multivariate_data | lmtp | Simulated Multivariate Exposure Data | data.frame | 2000 | 6 |
sim_cens | lmtp | Simulated Longitudinal Data With Censoring | data.frame | 1000 | 7 |
sim_point_surv | lmtp | Simulated Point-treatment Survival Data | data.frame | 2000 | 15 |
sim_t4 | lmtp | Simulated Longitudinal Data | data.frame | 5000 | 10 |
sim_timevary_surv | lmtp | Simulated Time-varying Survival Data | data.table | 500 | 11 |
holes | cocons | Holes Data Set | list | | |
stripes | cocons | Stripes Data Set | list | | |
occurrences | ppgm | Sceloporus occurrence data | data.frame | 18658 | 22 |
paleoclimate | ppgm | Paleoclimate Data for ppgm examples | list | | |
sampletrees | ppgm | Sample of Sceloporus phylogenies | multiPhylo | | |
scel_fossils | ppgm | Sceloporus fossil data | matrix | 45 | 4 |
BCdata | ltable | Breast cancer data to model risk | data.frame | 77 | 4 |
SMdata | ltable | Heart surgery data to model standardized (mortality) ratio. | list | | |
SimData | ltable | Simulated interval censored survival data to model hazard. | data.frame | 7 | 7 |
sdata | ltable | Simple Data. | data.frame | 22 | 4 |
tdata | ltable | Tromboembolism Data. | data.frame | 8 | 4 |
fleet1 | dbglm | Data of vehicles registered in New Zealand as of November 2017 | tbl_df | 10000 | 6 |
Agrupadas | RcmdrPlugin.TeachStat | Grouped or tabulated data set | data.frame | 4 | 3 |
Depositos | RcmdrPlugin.TeachStat | Deposits with credit institutions in Ourense | data.frame | 17 | 4 |
Prices | RcmdrPlugin.TeachStat | Data for computing price indices. | data.frame | 15 | 4 |
cars93 | RcmdrPlugin.TeachStat | Data from 93 Cars on Sale in the USA in 1993 | data.frame | 93 | 26 |
toydata | mstDIF | A Toy Example of 1000 Respondents Working on a Multistage Test | list | | |
simulated_data_1 | BayesBP | Generate simulated data 1 | list | | |
simulated_data_2 | BayesBP | Generate simulated data 2 | list | | |
LD.wiki34 | bigsnpr | Long-range LD regions | data.frame | 34 | 4 |
ACTG175 | mets | ACTG175, block randmized study from speff2trial package | data.frame | 2139 | 28 |
TRACE | mets | The TRACE study group of myocardial infarction | data.frame | 1878 | 9 |
base1cumhaz | mets | rate of CRBSI for HPN patients of Copenhagen | data.frame | 1076 | 2 |
base44cumhaz | mets | rate of Occlusion/Thrombosis complication for catheter of HPN patients of Copenhagen | data.frame | 58 | 2 |
base4cumhaz | mets | rate of Mechanical (hole/defect) complication for catheter of HPN patients of Copenhagen | data.frame | 170 | 2 |
bmt | mets | The Bone Marrow Transplant Data | data.frame | 408 | 5 |
calgb8923 | mets | CALGB 8923, twostage randomization SMART design | data.frame | 593 | 27 |
dermalridges | mets | Dermal ridges data (families) | data.frame | 106 | 10 |
dermalridgesMZ | mets | Dermal ridges data (monozygotic twins) | data.frame | 36 | 5 |
diabetes | mets | The Diabetic Retinopathy Data | data.frame | 394 | 7 |
drcumhaz | mets | Rate for leaving HPN program for patients of Copenhagen | data.frame | 386 | 2 |
ghaplos | mets | ghaplos haplo-types for subjects of haploX data | data.frame | 555 | 4 |
hapfreqs | mets | hapfreqs data set | data.frame | 19 | 3 |
haploX | mets | haploX covariates and response for haplo survival discrete survival | data.frame | 2003 | 9 |
melanoma | mets | The Melanoma Survival Data | data.frame | 205 | 6 |
mena | mets | Menarche data set | data.frame | 2000 | 7 |
migr | mets | Migraine data | data.frame | 4065 | 6 |
multcif | mets | Multivariate Cumulative Incidence Function example data set | data.frame | 400 | 8 |
np | mets | np data set | data.frame | 10000 | 7 |
prt | mets | Prostate data set | data.frame | 29222 | 6 |
sTRACE | mets | The TRACE study group of myocardial infarction | data.frame | 500 | 9 |
tTRACE | mets | The TRACE study group of myocardial infarction | data.frame | 1000 | 9 |
ttpd | mets | ttpd discrete survival data on interval form | data.frame | 1000 | 6 |
twinbmi | mets | BMI data set | data.frame | 11188 | 7 |
twinstut | mets | Stutter data set | data.frame | 32894 | 6 |
Tax4Fun2_KEGG | microeco | The KEGG data files used in the trans_func class | list | | |
dataset | microeco | The dataset structured with microtable class for the demonstration of examples | microtable | | |
env_data_16S | microeco | The environmental factors for the 16S example data | data.frame | 200 | 11 |
fungi_func_FUNGuild | microeco | The FUNGuild database for fungi trait prediction | data.frame | 13017 | 9 |
fungi_func_FungalTraits | microeco | The FungalTraits database for fungi trait prediction | data.frame | 10771 | 24 |
otu_table_16S | microeco | The OTU table of the 16S example data | data.frame | 13628 | 90 |
otu_table_ITS | microeco | The OTU table of the ITS example data | data.frame | 323 | 309 |
phylo_tree_16S | microeco | The phylogenetic tree of 16S example data | phylo | | |
prok_func_FAPROTAX | microeco | The modified FAPROTAX trait database | list | | |
prok_func_NJC19_list | microeco | The modified NJC19 database | list | | |
sample_info_16S | microeco | The sample information of 16S example data | data.frame | 90 | 4 |
sample_info_ITS | microeco | The sample information of ITS example data | data.frame | 309 | 33 |
taxonomy_table_16S | microeco | The taxonomic information of 16S example data | data.frame | 13628 | 7 |
taxonomy_table_ITS | microeco | The taxonomic information of ITS example data | data.frame | 323 | 7 |
MNImap_hip | VertexWiseR | Hippocampal surface in MNI space | MNIsurface | | |
ROImap_fs5 | VertexWiseR | Atlas parcellations of fsaverage5 | ROImap | | |
ROImap_fs6 | VertexWiseR | Atlas parcellations of fsaverage6 | ROImap | | |
ROImap_fslr32k | VertexWiseR | Atlas parcellations of FS_LR32k | ROImap | | |
ROImap_hip | VertexWiseR | Atlas parcellations of the hippocampus (CITI168) | ROImap | | |
edgelist_hip | VertexWiseR | List of edges for the hippocampal template | edgelist | | |
fs6_to_fs5_map | VertexWiseR | fsaverage6 template object for nearest neighbor conversion in fs6_to_fs5() | numeric | | |
hip_points_cells | VertexWiseR | points and cells data required to build the hippocampus surface template | list | | |
binnenveld | OBIC | Example dataset for use in OBIC package | data.table | 3251 | 55 |
bouwsteen_tb | OBIC | Table with water retention properties of 'bouwstenen' | data.table | 36 | 14 |
column_description.obic | OBIC | Column description for the OBIC | data.table | 216 | 6 |
crops.makkink | OBIC | Makkink correction factor table | data.table | 24 | 13 |
crops.obic | OBIC | Linking table between crops and different functions in OBIC | data.table | 521 | 22 |
eval.crumbleability | OBIC | Coefficient table for evaluating crumbleability | data.table | 16 | 4 |
management.obic | OBIC | Relational table linking soil management measures to ecosystem services | data.table | 15 | 6 |
nema.crop.rot.obic | OBIC | Damage and reproduction of soil-borne pathogens and pests on crops | data.table | 7059 | 21 |
nema.obic | OBIC | Nematode table | data.table | 78 | 7 |
nleach_table | OBIC | Table with fractions of excess N which runs off to groundwater and surface water | data.table | 198 | 7 |
recom.obic | OBIC | Applicability range of measures, including literature based estimates, of effects on soil indicators | data.table | 4048 | 11 |
recom.obic_bkp | OBIC | Effects of measures on soil indicators | data.table | 9152 | 11 |
season.obic | OBIC | Desired growing season period for maximum yield | data.table | 116 | 6 |
soils.obic | OBIC | Linking table between soils and different functions in OBIC | data.table | 9 | 4 |
tbl.ph.delta | OBIC | Table with optimal pH for different crop plans | data.table | 136 | 10 |
waterstress.obic | OBIC | Linking table between crops, soils, groundwater tables and water induced stresses in OBIC | data.table | 393680 | 6 |
weather.obic | OBIC | Weather table | data.table | 12 | 4 |
weight.obic | OBIC | Weight of indicators to calculate integrated scores | data.table | 196 | 5 |
example_binary | scoringutils | Binary forecast example data | forecast_binary | 1031 | 9 |
example_nominal | scoringutils | Nominal example data | forecast_nominal | 3093 | 10 |
example_point | scoringutils | Point forecast example data | forecast_point | 1031 | 9 |
example_quantile | scoringutils | Quantile example data | forecast_quantile | 20545 | 10 |
example_sample_continuous | scoringutils | Continuous forecast example data | forecast_sample | 35624 | 10 |
example_sample_discrete | scoringutils | Discrete forecast example data | forecast_sample | 35624 | 10 |
intcal | rintcal | IntCal20 json file | list | | |
fish | insight | Sample data set | data.frame | 250 | 9 |
adams_bt_03 | ypr | Adams Lake Bull Trout Population Parameters (2003) | ypr_population | | |
chilliwack_bt_05 | ypr | Chilliwack Lake Bull Trout Populations Parameters (2005) | ypr_populations | | |
kootenay_bt_13 | ypr | Kootenay Lake Bull Trout Population Parameters (2013) | ypr_population | | |
kootenay_rb | ypr | Kootenay Lake Rainbow Trout Population Parameters | ypr_population | | |
kootenay_rb_13 | ypr | Kootenay Lake Rainbow Trout Population Parameters (2013) | ypr_population | | |
quesnel_bt | ypr | Quesnel Lake Bull Trout Population Parameters | ypr_population | | |
quesnel_lt | ypr | Quesnel Lake Lake Trout Population Parameters | ypr_population | | |
quesnel_rb | ypr | Quesnel Lake Rainbow Trout Population Parameters | ypr_population | | |
agri_studies | NaileR | Agribusiness studies survey | data.frame | 53 | 42 |
beard | NaileR | Beard descriptions | tbl_df | 494 | 2 |
beard_cont | NaileR | Beard descriptions | data.frame | 8 | 335 |
beard_wide | NaileR | Beard descriptions | data.frame | 8 | 24 |
boss | NaileR | Ideal boss survey | data.frame | 73 | 39 |
glossophobia | NaileR | Glossophobia survey | data.frame | 139 | 41 |
local_food | NaileR | Local food systems survey | data.frame | 573 | 63 |
nutriscore | NaileR | Nutri-score survey | data.frame | 112 | 36 |
quality | NaileR | Perception of food quality | tbl_df | 55 | 9 |
waste | NaileR | Food waste survey | data.frame | 180 | 77 |
bcch | naturecounts | Example black-capped chickadee data | data.frame | 160 | 57 |
hofi | naturecounts | Example house finch data | data.frame | 19 | 57 |
NLD_muni | tmap | World and Netherlands map | sf | 403 | 15 |
NLD_prov | tmap | World and Netherlands map | sf | 12 | 14 |
World | tmap | World and Netherlands map | sf | 177 | 16 |
land | tmap | Spatial data of global land cover | stars | | |
metro | tmap | Spatial data of metropolitan areas | sf | 436 | 13 |
rivers | tmap | Spatial data of rivers | sf | 1616 | 5 |
TPB | modsem | TPB | data.frame | 2000 | 15 |
TPB_UK | modsem | TPB_UK | data.frame | 1169 | 20 |
jordan | modsem | Jordan subset of PISA 2006 data | data.frame | 6038 | 15 |
oneInt | modsem | oneInt | data.frame | 2000 | 9 |
rxReservedKeywords | rxode2 | A list and description of rxode2 supported reserved keywords | data.frame | 31 | 3 |
rxResidualError | rxode2 | A description of Rode2 supported residual errors | data.frame | 181 | 6 |
rxSyntaxFunctions | rxode2 | A list and description of Rode supported syntax functions | data.frame | 102 | 3 |
CpG2Gene | methylGSA | An example of user user-supplied mapping between CpGs and genes | data.frame | 364645 | 2 |
GS.list | methylGSA | An example of user input gene sets | list | | |
cpg.pval | methylGSA | An example of user input cpg.pval | numeric | | |
lcarsdata | lcars | LCARS colors | data.frame | 33 | 3 |
cross_blended_hypsometric_tints_db | tidyterra | Cross-blended hypsometric tints | tbl_df | 41 | 6 |
grass_db | tidyterra | GRASS color tables | tbl_df | 2920 | 6 |
hypsometric_tints_db | tidyterra | Hypsometric palettes database | tbl_df | 1102 | 6 |
princess_db | tidyterra | Princess palettes database | tbl_df | 75 | 5 |
volcano2 | tidyterra | Updated topographic information on Auckland's Maungawhau volcano | matrix | 174 | |
rADTTE | teal.modules.hermes | Random Time to Event Analysis Dataset | tbl_df | 2000 | 67 |
Sample_disease_gene_set | RVA | This is data to be included in package | data.frame | 1800 | 6 |
Sample_summary_statistics_table | RVA | This is data to be included in package | data.frame | 12045 | 6 |
Sample_summary_statistics_table1 | RVA | This is data to be included in package | data.frame | 12045 | 6 |
c2BroadSets | RVA | This is data to be included in package | GeneSetCollection | | |
count_table | RVA | This is data to be included in package | data.frame | 3934 | 164 |
sample_annotation | RVA | This is data to be included in package | data.frame | 164 | 6 |
sample_count_cpm | RVA | This is data to be included in package | data.frame | 4 | 164 |
wpA2020 | RVA | This is data to be included in package | data.frame | 26693 | 5 |
trekpals | trekcolors | Star Trek color palettes. | list | | |
trekfonts | trekfont | Available Star Trek fonts. | character | | |
anchor.case | cholera | Anchor or base case of each stack of fatalities. | data.frame | 578 | 2 |
border | cholera | Numeric IDs of line segments that create the map's border frame. | numeric | | |
fatalities | cholera | Amended Dodson and Tobler's cholera data. | data.frame | 578 | 5 |
fatalities.address | cholera | "Unstacked" amended cholera data with address as unit of observation. | data.frame | 321 | 6 |
fatalities.unstacked | cholera | "Unstacked" amended cholera fatalities data with fatality as unit of observation. | data.frame | 578 | 5 |
frame.data | cholera | Map frame data c("x", "y") and c("lon", "lat"). | data.frame | 106 | 8 |
frame.sample | cholera | Partitioned map frame points (segment endpoints). | list | | |
landmark.squares | cholera | Centers of city squares. | data.frame | 2 | 4 |
landmark.squaresB | cholera | Centers of city squares. | data.frame | 2 | 6 |
landmarks | cholera | Orthogonal projection of landmarks onto road network. | data.frame | 19 | 12 |
landmarksB | cholera | Landmark coordinates. | data.frame | 20 | 11 |
latlong.ortho.addr | cholera | Orthogonal projection of observed address (latlong) cases onto road network. | data.frame | 321 | 7 |
latlong.ortho.pump | cholera | Orthogonal projection of 13 original pumps (latlong). | data.frame | 13 | 7 |
latlong.ortho.pump.vestry | cholera | Orthogonal projection of the 14 pumps from the Vestry Report (latlong). | data.frame | 14 | 7 |
latlong.regular.cases | cholera | "Expected" cases (latlong). | data.frame | 19993 | 4 |
latlong.sim.ortho.proj | cholera | Road "address" of simulated (i.e., "expected") cases (latlong). | data.frame | 19993 | 8 |
ortho.proj | cholera | Orthogonal projection of observed cases onto road network. | data.frame | 578 | 5 |
ortho.proj.pump | cholera | Orthogonal projection of 13 original pumps. | data.frame | 13 | 6 |
ortho.proj.pump.vestry | cholera | Orthogonal projection of the 14 pumps from the Vestry Report. | data.frame | 14 | 6 |
oxford.weather | cholera | Oxford monthly weather data, January 1853 - February 2024. | data.frame | 2054 | 9 |
plague.pit | cholera | Plague pit coordinates. | data.frame | 13 | 2 |
pumps | cholera | Dodson and Tobler's pump data with street name. | data.frame | 13 | 6 |
pumps.vestry | cholera | Vestry report pump data. | data.frame | 14 | 6 |
rd.sample | cholera | Sample of road intersections (segment endpoints). | list | | |
rectangle.filter | cholera | Rectangular filter data. | data.frame | 4 | 2 |
regular.cases | cholera | "Expected" cases. | data.frame | 19993 | 2 |
road.segments | cholera | Dodson and Tobler's street data transformed into road segments. | data.frame | 658 | 7 |
roads | cholera | Dodson and Tobler's street data with appended road names. | data.frame | 1243 | 8 |
sim.ortho.proj | cholera | Road "address" of simulated (i.e., "expected") cases. | data.frame | 19993 | 6 |
sim.pump.case | cholera | List of "simulated" fatalities grouped by walking-distance pump neighborhood. | list | | |
sim.walking.distance | cholera | Walking distance to Broad Street Pump (#7). | data.frame | 19899 | 5 |
snow.neighborhood | cholera | Snow neighborhood fatalities. | numeric | | |
voronoi.polygons | cholera | Coordinates of Voronoi polygon vertices for original map. | list | | |
voronoi.polygons.vestry | cholera | Coordinates of Voronoi polygon vertices for Vestry Report map. | list | | |
stBooks | rtrek | Star Trek novel metadata. | tbl_df | 783 | 11 |
stGeo | rtrek | Raster grid location data for stellar cartographic map tile sets. | tbl_df | 18 | 4 |
stLogos | rtrek | Star Trek logos metadata. | tbl_df | 236 | 3 |
stSeries | rtrek | Star Trek series. | tbl_df | 35 | 3 |
stSpecies | rtrek | Species names and avatars, linked primarily from Memory Alpha. | tbl_df | 9 | 2 |
stTiles | rtrek | Available Star Trek map tile sets. | tbl_df | 2 | 8 |
stapiEntities | rtrek | Star Trek API entities. | tbl_df | 40 | 4 |
tlBooks | rtrek | Star Trek novel-based timeline. | tbl_df | 2122 | 14 |
tlEvents | rtrek | Star Trek event-based timeline. | tbl_df | 1241 | 6 |
tlFootnotes | rtrek | Star Trek timeline footnotes. | tbl_df | 605 | 3 |
superheroes_supertbl | REDCapTidieR | Superheroes Data | redcap_supertbl | 2 | 9 |
bcm | oppar | Breast cancer metastases from different anatomical sites | ExpressionSet | | |
eset | oppar | Tomlins et al. Prostate Cancer data (GEO: GSE6099) | ExpressionSet | | |
maupin | oppar | Maupin's TGFb data and a TGFb gene signature | list | | |
fs_prices | piar | Price data | data.frame | 40 | 5 |
fs_weights | piar | Price data | data.frame | 5 | 2 |
ms_prices | piar | Price data | data.frame | 40 | 4 |
ms_weights | piar | Price data | data.frame | 5 | 3 |
miami | shapviz | Miami-Dade County House Prices | data.frame | 13932 | 17 |
osm_highway_values | pavement | Values for the 'highway' tag in OpenStreetMap data | character | | |
sample_accidents | pavement | Sample accidents data | sf | 10 | 5 |
sample_roads | pavement | Sample roads data | sf | 6 | 3 |
dists | qtlmt | Data sets | data.frame | 12 | 3 |
eps | qtlmt | Data sets | data.frame | 1 | 3 |
eqtl | qtlmt | Data sets | data.frame | 12 | 18 |
gmap | qtlmt | Data sets | data.frame | 95 | 4 |
maps | qtlmt | Data sets | data.frame | 95 | 6 |
markers | qtlmt | Data sets | matrix | 211 | 95 |
mdat | qtlmt | Data sets | matrix | 211 | 95 |
mpos | qtlmt | Data sets | data.frame | 95 | 4 |
qtl | qtlmt | Data sets | list | | |
traits | qtlmt | Data sets | matrix | 211 | 16 |
v | qtlmt | Data sets | list | | |
xid | qtlmt | Data sets | list | | |
dvs_ivs | semhelpinghands | Sample Dataset: 3 Predictors and 3 Outcomes | data.frame | 100 | 7 |
simple_mediation | semhelpinghands | Sample Dataset: Simple Mediation | data.frame | 100 | 4 |
Function_1_dummy | lab2clean | Dummy Data for demonstrating function 1 | data.frame | 87 | 2 |
Function_2_dummy | lab2clean | Dummy Data for demonstrating function 2 | data.frame | 86863 | 5 |
common_words | lab2clean | Data for the common words | data.frame | 19 | 9 |
logic_rules | lab2clean | Data for the logic rules | data.table | 18 | 4 |
reportable_interval | lab2clean | Data for the reportable interval | data.table | 493 | 4 |
FIFA2018 | distributions3 | Goals scored in all 2018 FIFA World Cup matches | data.frame | 128 | 7 |
canyon_wren | dynaSpec | Acoustic recording of a _Catherpes mexicanus_ (canyon wren) song. | Wave | | |
grid | geosimilarity | Spatial grid data of explanatory variables. | tbl_df | 13132 | 12 |
zn | geosimilarity | Spatial datasets of trace element Zn. | tbl_df | 894 | 12 |
chatgpt | volker | ChatGPT Adoption Dataset CG-GE-APR23 | tbl_df | 101 | 19 |
class | matlib | Class Data Set | data.frame | 15 | 4 |
therapy | matlib | Therapy Data | data.frame | 10 | 4 |
workers | matlib | Workers Data | data.frame | 10 | 4 |
COL.OLD | spdep | Columbus OH spatial analysis data set - old numbering | data.frame | 49 | 22 |
COL.nb | spdep | Columbus OH spatial analysis data set - old numbering | nb | | |
bbs | spdep | Columbus OH spatial analysis data set | matrix | 49 | |
col.gal.nb | spdep | Columbus OH spatial analysis data set | nb | | |
columbus | spdep | Columbus OH spatial analysis data set | data.frame | 49 | 22 |
coords | spdep | Columbus OH spatial analysis data set | matrix | 49 | |
eire.coords.utm | spdep | Eire data sets | data.frame | 26 | 2 |
eire.df | spdep | Eire data sets | data.frame | 26 | 9 |
eire.nb | spdep | Eire data sets | nb | | |
eire.polys.utm | spdep | Eire data sets | polylist | | |
polys | spdep | Columbus OH spatial analysis data set | polylist | | |
Schneider2017 | diagmeta | Meta-analysis of studies of the diagnostic test accuracy of FENO for diagnosis of asthma | data.frame | 150 | 9 |
NBthDEmod2 | GeoDiff | A demo example output list returned by function fitNBthDE | list | | |
NBthmDEmod2 | GeoDiff | A demo example output list returned by function fitNBthmDE | list | | |
NBthmDEmod2slope | GeoDiff | A demo example output list returned by function fitNBthmDE | list | | |
demoData | GeoDiff | A demo dataset for GeoMx Cancer Transcriptome Atlas (CTA) panel | NanoStringGeoMxSet | | |
kidney | GeoDiff | A demo dataset for GeoMx Human Whole Transcriptome Atlas (WTA) panel | NanoStringGeoMxSet | | |
FEV | coneproj | Forced Expiratory Volume | data.frame | 654 | 5 |
TwoDamat | coneproj | A Two Dimensional Constraint Matrix | matrix | 324 | |
cubic | coneproj | A Data Set for the Example of the Qprog Function | data.frame | 50 | 2 |
feet | coneproj | Foot Measurements for Fourth Grade Children | data.frame | 39 | 8 |
hbef2015 | spOccupancy | Detection-nondetection data of 12 foliage gleaning bird species in 2015 in the Hubbard Brook Experimental Forest | list | | |
hbefElev | spOccupancy | Elevation in meters extracted at a 30m resolution across the Hubbard Brook Experimental Forest | data.frame | 46090 | 3 |
hbefTrends | spOccupancy | Detection-nondetection data of 12 foliage gleaning bird species from 2010-2018 in the Hubbard Brook Experimental Forest | list | | |
neon2015 | spOccupancy | Detection-nondetection data of 12 foliage gleaning bird species in 2015 in Bartlett Experimental Forest in New Hampshire, USA | list | | |
L | HEMDAG | Small real example datasets | matrix | 100 | 23 |
S | HEMDAG | Small real example datasets | matrix | 100 | 23 |
W | HEMDAG | Small real example datasets | matrix | 100 | 100 |
g | HEMDAG | Small real example datasets | graphNEL | | |
test.index | HEMDAG | Small real example datasets | integer | | |
pbmc1 | scAnnotate | pbmc1 | data.frame | 598 | 2001 |
pbmc2 | scAnnotate | pbmc2 | data.frame | 644 | 2001 |
predict_label | scAnnotate | predict_label | character | | |
hg19pvalues | metaseqR2 | p-values from human RNA-Seq data with two conditions, four samples | matrix | 1000 | 9 |
libsizeListMm9 | metaseqR2 | Mouse RNA-Seq data with two conditions, four samples | list | | |
mm9GeneCounts | metaseqR2 | Mouse RNA-Seq data with two conditions, four samples | data.frame | 3787 | 12 |
sampleListMm9 | metaseqR2 | Mouse RNA-Seq data with two conditions, four samples | list | | |
filenm | iCNV | Name of the file | character | | |
icnv_res0 | iCNV | Example iCNV calling results. | list | | |
ngs_baf | iCNV | BAF list from NGS | list | | |
ngs_baf.chr | iCNV | BAF chromosome from NGS | list | | |
ngs_baf.id | iCNV | BAF variants id from NGS | list | | |
ngs_baf.nm | iCNV | BAF variants sample name from NGS | list | | |
ngs_baf.pos | iCNV | BAF position list from NGS | list | | |
ngs_plr | iCNV | Normalized Poisson likelihood ratio list from NGS | list | | |
ngs_plr.pos | iCNV | Exon location list from NGS | list | | |
normObj | iCNV | Demo data pre-stored for normObj. | list | | |
qcObj | iCNV | Demo data pre-stored for qcObj. | list | | |
sampname | iCNV | CODEX sample name | matrix | 46 | 1 |
sampname_qc | iCNV | QCed sample name | character | | |
snp_baf | iCNV | BAF list from Array | list | | |
snp_baf.pos | iCNV | BAF position list from Array | list | | |
snp_lrr | iCNV | Normalized log R ratio list from Array | list | | |
snp_lrr.pos | iCNV | SNP position list from Array | list | | |
diabetesData | spicyR | Diabetes IMC data in SCE format. | SingleCellExperiment | | |
spicyTest | spicyR | Results from spicy for diabetesData | SpicyResults | | |
EC | GOplot | Transcriptomic information of endothelial cells. | list | | |
CarTask | betareg | Partition-Primed Probability Judgement Task for Car Dealership | data.frame | 155 | 3 |
FoodExpenditure | betareg | Proportion of Household Income Spent on Food | data.frame | 38 | 3 |
GasolineYield | betareg | Estimation of Gasoline Yields from Crude Oil | data.frame | 32 | 6 |
ImpreciseTask | betareg | Imprecise Probabilities for Sunday Weather and Boeing Stock Task | data.frame | 242 | 3 |
LossAversion | betareg | (No) Myopic Loss Aversion in Adolescents | data.frame | 570 | 7 |
MockJurors | betareg | Confidence of Mock Jurors in Their Verdicts | data.frame | 104 | 3 |
ReadingSkills | betareg | Dyslexia and IQ Predicting Reading Accuracy | data.frame | 44 | 4 |
StressAnxiety | betareg | Dependency of Anxiety on Stress | data.frame | 166 | 2 |
WeatherTask | betareg | Weather Task with Priming and Precise and Imprecise Probabilities | data.frame | 345 | 3 |
CRT2 | WebPower | Example Data For CRT With 2 Arms | data.frame | 8 | 4 |
CRT3 | WebPower | Example Data For CRT With 3 Arms | data.frame | 30 | 4 |
MRT2 | WebPower | Example Data For MRT With 2 Arms | data.frame | 16 | 4 |
MRT3 | WebPower | Example Data For MRT With 3 Arms | data.frame | 24 | 4 |
forest.fire | mar1s | Forest fire in Irkutsk region, USSR: historical data | ts | | |
nesterov.index | mar1s | Nesterov index in Irkutsk region, USSR: historical data | mts | 8030 | 7 |
model_db | parsnip | parsnip model specification database | tbl_df | 105 | 7 |
allowed_inputs | dynwrap | All allowed inputs for a TI method | tbl_df | 16 | 2 |
allowed_outputs | dynwrap | All allowed outputs for a TI method | tbl_df | 14 | 5 |
example_dataset | dynwrap | Example dataset | dynwrap::with_dimred | | |
example_trajectory | dynwrap | Example trajectory | dynwrap::with_dimred | | |
prior_usages | dynwrap | Metadata on prior usages | tbl_df | 3 | 2 |
priors | dynwrap | Metadata on priors | tbl_df | 13 | 6 |
trajectory_type_dag | dynwrap | A DAG connecting different trajectory types | tbl_graph | | |
trajectory_types | dynwrap | Metadata on the trajectory types | tbl_df | 9 | 6 |
wrapper_types | dynwrap | Metadata on wrapper types | tbl_df | 7 | 4 |
Acheron | hydrostats | Acheron River flow data | data.frame | 10944 | 2 |
cooper | hydrostats | | data.frame | 7670 | 2 |
ausgdp | expsmooth | Quarterly Australian GDP | ts | | |
bonds | expsmooth | Monthly US government bond yields | ts | | |
cangas | expsmooth | Monthly Canadian gas production | ts | | |
carparts | expsmooth | Monthly sales car parts | mts | 51 | 2674 |
dji | expsmooth | Monthly Dow Jones Index | mts | 207 | 4 |
djiclose | expsmooth | Monthly Dow Jones Index: closing | mts | 951 | 2 |
enplanements | expsmooth | Monthly US domestic enplanements | ts | | |
fmsales | expsmooth | Weekly FM sales | ts | | |
freight | expsmooth | Annual US new freight cars | ts | | |
frexport | expsmooth | Quarterly French exports | ts | | |
gasprice | expsmooth | US gasoline prices | mts | 191 | 2 |
hospital | expsmooth | Monthly patient count | mts | 84 | 767 |
jewelry | expsmooth | Weekly jewelry sales | mts | 124 | |
mcopper | expsmooth | Monthly copper prices | ts | | |
msales | expsmooth | Monthly product sales | mts | 36 | 2 |
partx | expsmooth | Monthly sales of an automobile part | ts | | |
ukcars | expsmooth | Quarterly UK passenger car production | ts | | |
unemp.cci | expsmooth | Unemployment and the CCI | mts | 100 | 3 |
usgdp | expsmooth | Quarterly US GDP | ts | | |
usnetelec | expsmooth | Annual US net electricity generation | ts | | |
utility | expsmooth | Hourly utility demand | ts | | |
vehicles | expsmooth | Hourly vehicle counts | ts | | |
visitors | expsmooth | Monthly Australian overseas vistors | ts | | |
xrates | expsmooth | Monthly exchange rates | mts | 77 | 2 |
coverage_res_chr21 | DegNorm | Example CoverageClass data | CoverageClass | | |
res_DegNorm_chr21 | DegNorm | Example DegNormClass data | DegNormClass | | |
regulon | epiregulon.extra | regulon created using 'epiregulon' package from reprogram-seq data | DFrame | | |
power_example | PoweREST | An example of power results with multiple replicates number | data.frame | 844 | 5 |
result_example | PoweREST | An example of power results from PoweREST | data.frame | 19386 | 3 |
AUSdata | spTDyn | Service functions and some undocumented functions for the spTimer library | data.frame | 1440 | 11 |
NYdata | spTDyn | Service functions and some undocumented functions for the spTimer library | data.frame | 1736 | 10 |
rhc_X | optrefine | Right Heart Catheterization Data | matrix | 5735 | 28 |
csd | RNAmodR | Example data in the RNAmodR package | CoverageSequenceData | | |
e3sd | RNAmodR | Example data in the RNAmodR package | End3SequenceData | | |
e5sd | RNAmodR | Example data in the RNAmodR package | End5SequenceData | | |
esd | RNAmodR | Example data in the RNAmodR package | EndSequenceData | | |
msi | RNAmodR | Example data in the RNAmodR package | ModSetInosine | | |
ne3sd | RNAmodR | Example data in the RNAmodR package | NormEnd3SequenceData | | |
ne5sd | RNAmodR | Example data in the RNAmodR package | NormEnd5SequenceData | | |
pesd | RNAmodR | Example data in the RNAmodR package | ProtectedEndSequenceData | | |
psd | RNAmodR | Example data in the RNAmodR package | PileupSequenceData | | |
sdl | RNAmodR | Example data in the RNAmodR package | SequenceDataList | | |
sds | RNAmodR | Example data in the RNAmodR package | SequenceDataSet | | |
shah1998 | bootf2 | Dissolution data from the article of Shah et al 1998 | list | | |
ammonia | forImage | Ammonia size data | tbl_df | 867 | 7 |
amphistegina | forImage | Amphistegina size data | tbl_df | 167 | 5 |
angulogerina | forImage | Angulogerina size data | tbl_df | 95 | 6 |
asterotrochammina | forImage | Asterotrochammina size data | tbl_df | 335 | 7 |
bolivina | forImage | Bolivina size data | tbl_df | 628 | 7 |
cibicidoides | forImage | Cibicidoides size data | tbl_df | 118 | 7 |
data_pco | forImage | Foraminiferal genera data for 'forImage' examples | tbl_df | 73 | 5 |
discorbinella | forImage | Discorbinella size data | tbl_df | 318 | 7 |
laevipeneroplis | forImage | Laevipeneroplis size data | tbl_df | 79 | 7 |
loxostomina | forImage | Loxostomina size data | tbl_df | 30 | 6 |
nonionella | forImage | Nonionella size data | tbl_df | 208 | 7 |
patellina | forImage | Patellina size data | tbl_df | 77 | 6 |
quinqueloculina | forImage | Quinqueloculina size data | tbl_df | 688 | 10 |
rectocibicides | forImage | Rectocibicides size data | tbl_df | 199 | 4 |
spirillina | forImage | Spirillina size data | spec_tbl_df | 41 | 6 |
textularia | forImage | Textularia size data | tbl_df | 84 | 7 |
ajmrzik16_col | dendata | Zika cases by municipality in the departament of Tolima, Colombia. | sf | 46 | 6 |
den_loc_mex | dendata | Dengue cases by AGEBs from nine locations in Mexico. | sf | 2174 | 16 |
CancerDetector.markers | cfTools | Cancer-specific marker parameter | data.frame | 1266 | 3 |
CancerDetector.reads | cfTools | Fragment-level methylation state for cancer detection | data.frame | 9991 | 2 |
CpG_OB_demo | cfTools | Methylation information for CpG on the original bottom strand (OB) | data.frame | 2224 | 5 |
CpG_OT_demo | cfTools | Methylation information for CpG on the original top strand (OT) | data.frame | 2556 | 5 |
beta_matrix | cfTools | Beta value matrix | data.frame | 20 | 3 |
cfDeconvolve.markers | cfTools | Tissue-specific marker parameter | data.frame | 10 | 8 |
cfDeconvolve.reads | cfTools | Fragment-level methylation state for tissue deconvolution | data.frame | 942 | 2 |
cfsort_markers | cfTools | cfSort markers | data.frame | 51035 | 4 |
cfsort_reads | cfTools | Fragment-level methylation state for cfSort tissue deconvolution | data.frame | 99999 | 2 |
demo.fragment_level.meth.bed | cfTools | Fragment-level methylation information | data.frame | 552 | 9 |
demo.refo_frag.bed | cfTools | Fragment-level information | data.frame | 559 | 6 |
demo.refo_meth.bed | cfTools | Methylation information on fragments | data.frame | 552 | 8 |
demo.sorted.bed | cfTools | Paired-end sequencing reads | data.frame | 1117 | 6 |
marker_index | cfTools | Marker name | data.frame | 3 | 1 |
markers.bed | cfTools | Genomic postions of markers | data.frame | 3 | 4 |
sample_type | cfTools | Sample type | data.frame | 20 | 1 |
ts_AR1_Gaussian | imputeFin | | list | | |
ts_AR1_t | imputeFin | | list | | |
ts_VAR_t | imputeFin | | list | | |
achv_color_map | gophr | OHA Achievement Colors | tbl_df | 4 | 3 |
cascade_ind | gophr | MER Clinical Cascade indicators | character | | |
snapshot_ind | gophr | MER Snapshot indicators | character | | |
sampleexp | IVAS | CEU expression data | data.frame | 64 | 78 |
samplesnp | IVAS | CEU genotype data | data.frame | 11 | 78 |
samplesnplocus | IVAS | snplocus | data.frame | 11 | 3 |
simuGene | geeVerse | A Simulated Genetic Data from HapGen2 | matrix | 1000 | 500 |
yeastG1 | geeVerse | A Subset of Yeast Cell Cycle Gene Expression Data (G1 Phase) | data.frame | 1132 | 99 |
fips_lookup | tpm | FIPS Codes | data.table | 56 | 4 |
sim.data | promotionImpact | Daily Total Sales | data.frame | 958 | 2 |
sim.promotion | promotionImpact | Promotion Schedule | data.frame | 50 | 4 |
sim.promotion.sales | promotionImpact | Daily Promotion Sales with Promotion information | data.frame | 1486 | 6 |
boa | ferrn | Simulated sine, pipe, and gaussian mixture | tbl_df | 1000 | 10 |
boa5 | ferrn | Simulated sine, pipe, and gaussian mixture | tbl_df | 1000 | 5 |
boa6 | ferrn | Simulated sine, pipe, and gaussian mixture | tbl_df | 1000 | 6 |
holes_1d_better | ferrn | Data objects collected during the projection pursuit optimisation | tbl_df | 79 | 8 |
holes_1d_geo | ferrn | Data objects collected during the projection pursuit optimisation | tbl_df | 416 | 8 |
holes_1d_jellyfish | ferrn | Data objects collected during the projection pursuit optimisation | tbl_df | 2500 | 8 |
holes_2d_better | ferrn | Data objects collected during the projection pursuit optimisation | tbl_df | 98 | 8 |
holes_2d_better_max_tries | ferrn | Data objects collected during the projection pursuit optimisation | tbl_df | 1499 | 8 |
pipe1000 | ferrn | Simulated sine, pipe, and gaussian mixture | matrix | 1000 | 6 |
pipe1000_10d | ferrn | Simulated sine, pipe, and gaussian mixture | matrix | 1000 | 10 |
pipe1000_12d | ferrn | Simulated sine, pipe, and gaussian mixture | matrix | 1000 | 12 |
pipe1000_8d | ferrn | Simulated sine, pipe, and gaussian mixture | matrix | 1000 | 8 |
sine1000 | ferrn | Simulated sine, pipe, and gaussian mixture | matrix | 1000 | 6 |
sine1000_8d | ferrn | Simulated sine, pipe, and gaussian mixture | matrix | 1000 | 8 |
retailsa | rjd3filters | Seasonally Adjusted Retail Sales | list | | |
jam_values | getACS | ACS Jam Values for Medians | tbl_df | 20 | 6 |
race_iteration | getACS | Race or Latino Origin Table Codes | tbl_df | 9 | 3 |
tigerweb_geo_index | getACS | U.S. Census Bureau ArcGIS Services Index | tbl_df | 7081 | 15 |
usa_states | getACS | U.S. States Reference Data | data.frame | 56 | 7 |
gap | RGAP | gap data set | list | | |
indicator | RGAP | Indicators fo CUBS | list | | |
ex_sales | hpiR | Subset of Seattle Home Sales | data.frame | 5348 | 16 |
seattle_sales | hpiR | Seattle Home Sales | data.frame | 43313 | 16 |
BMT | SemiCompRisks | Data on 137 Bone Marrow Transplant Patients | data.frame | 137 | 22 |
CIBMTR | SemiCompRisks | Center for International Blood and Bone Marrow Transplant Research (CIBMTR) data | data.frame | 9651 | 5 |
CIBMTR_Params | SemiCompRisks | Estimates for model parameters from semi-competing risks analysis of the CIBMTR data using Weibull illness-death model. | list | | |
scrData | SemiCompRisks | A simulated clustered semi-competing risks data set | data.frame | 2000 | 8 |
survData | SemiCompRisks | A simulated clustered univariate survival data. | data.frame | 5500 | 5 |
openxlsxFontSizeLookupTable | openxlsx | Font Size Lookup tables | data.frame | 29 | 225 |
openxlsxFontSizeLookupTableBold | openxlsx | Font Size Lookup tables | data.frame | 29 | 225 |
isotopes_ds | eprscope | Nuclear Isotope Data Frame (Dataset) with ENDOR Frequencies | data.table | 351 | 9 |
solvents_ds | eprscope | Solvent Properties Data Frame (Dataset) for EPR/ENDOR | tbl_df | 46 | 10 |
pftmapping | PEcAn.ED2 | Mapping of PEcAn PFT names to ED2 PFT numbers | data.frame | 73 | 2 |
col | PEcAn.all | | character | | |
na_version | PEcAn.all | | package_version | | |
pecan_releases | PEcAn.all | Dates, tags, and versions of all PEcAn releases | data.frame | 33 | 3 |
pecan_version_history | PEcAn.all | Versions of all PEcAn packages in each release of PEcAn | data.frame | 53 | 34 |
strict | PEcAn.all | | logical | | |
CH_migration_data | flowmapper | CH_migration_data | tbl_df | 325 | 8 |
cantons | flowmapper | cantons | sf | 26 | 2 |
anole.data | phytools | Phylogenetic datasets | data.frame | 82 | 6 |
anoletree | phytools | Phylogenetic datasets | simmap | | |
ant.geog | phytools | Phylogenetic datasets | factor | | |
ant.tree | phytools | Phylogenetic datasets | phylo | | |
bat.tree | phytools | Phylogenetic datasets | phylo | | |
bat_virus.data | phytools | Phylogenetic datasets | data.frame | 17 | 2 |
betaCoV.tree | phytools | Phylogenetic datasets | phylo | | |
bonyfish.data | phytools | Phylogenetic datasets | data.frame | 90 | 2 |
bonyfish.tree | phytools | Phylogenetic datasets | phylo | | |
butterfly.data | phytools | Phylogenetic datasets | data.frame | 287 | 1 |
butterfly.tree | phytools | Phylogenetic datasets | phylo | | |
cordylid.data | phytools | Phylogenetic datasets | data.frame | 28 | 3 |
cordylid.tree | phytools | Phylogenetic datasets | phylo | | |
darter.tree | phytools | Phylogenetic datasets | phylo | | |
eel.data | phytools | Phylogenetic datasets | data.frame | 61 | 2 |
eel.tree | phytools | Phylogenetic datasets | phylo | | |
elapidae.tree | phytools | Phylogenetic datasets | phylo | | |
flatworm.data | phytools | Phylogenetic datasets | data.frame | 28 | 1 |
flatworm.tree | phytools | Phylogenetic datasets | phylo | | |
liolaemid.data | phytools | Phylogenetic datasets | data.frame | 258 | 3 |
liolaemid.tree | phytools | Phylogenetic datasets | phylo | | |
mammal.data | phytools | Phylogenetic datasets | data.frame | 49 | 2 |
mammal.geog | phytools | Phylogenetic datasets | matrix | 72 | 2 |
mammal.tree | phytools | Phylogenetic datasets | phylo | | |
primate.data | phytools | Phylogenetic datasets | data.frame | 90 | 6 |
primate.tree | phytools | Phylogenetic datasets | phylo | | |
salamanders | phytools | Phylogenetic datasets | phylo | | |
sunfish.data | phytools | Phylogenetic datasets | data.frame | 28 | 3 |
sunfish.tree | phytools | Phylogenetic datasets | simmap | | |
tortoise.geog | phytools | Phylogenetic datasets | data.frame | 15 | 2 |
tortoise.tree | phytools | Phylogenetic datasets | phylo | | |
tropidurid.data | phytools | Phylogenetic datasets | data.frame | 76 | 2 |
tropidurid.tree | phytools | Phylogenetic datasets | simmap | | |
vertebrate.data | phytools | Phylogenetic datasets | data.frame | 11 | 3 |
vertebrate.tree | phytools | Phylogenetic datasets | phylo | | |
wasp.data | phytools | Phylogenetic datasets | data.frame | 15 | 2 |
wasp.trees | phytools | Phylogenetic datasets | multiPhylo | | |
whale.tree | phytools | Phylogenetic datasets | phylo | | |
community_data | forstringr | Data containing whitespaces | tbl_df | 33 | 8 |
richest_in_nigeria | forstringr | Rank of billionaires in Nigeria | tbl_df | 10 | 5 |
domain_list | domainator | Domain list classification of domains into news,portals, search, and social media | data.frame | 663 | 2 |
news_types | domainator | News Types | data.frame | 690 | 2 |
online_news | domainator | Domain list of online news | spec_tbl_df | 542 | 2 |
us_news | domainator | Domain list of us news contains a list of and information on 5,397 US news domains. The domains overwhelmingly represent US-based organizations, but since the list was partly sourced from browsing data, it also includes some international domains visited by US study participants. | spec_tbl_df | 5397 | 3 |
covid19_sa | epichains | COVID-19 Data Repository for South Africa | tbl_df | 14 | 2 |
library_census | svrep | Public Libraries Survey (PLS): A Census of U.S. Public Libraries in FY2020 | tbl_df | 9245 | 23 |
library_multistage_sample | svrep | Public Libraries Survey (PLS): A Census of U.S. Public Libraries in FY2020 | tbl_df | 193 | 30 |
library_stsys_sample | svrep | Public Libraries Survey (PLS): A Census of U.S. Public Libraries in FY2020 | tbl_df | 219 | 27 |
lou_pums_microdata | svrep | ACS PUMS Data for Louisville | tbl_df | 80 | 86 |
lou_vax_survey | svrep | Louisville Vaccination Survey | tbl_df | 1000 | 6 |
lou_vax_survey_control_totals | svrep | Control totals for the Louisville Vaccination Survey | list | | |
FLUXNET.sitemap | PEcAn.data.atmosphere | | data.frame | 698 | 2 |
Lat | PEcAn.data.atmosphere | | array | | |
Lat | PEcAn.data.atmosphere | | array | | |
Lon | PEcAn.data.atmosphere | | array | | |
Lon | PEcAn.data.atmosphere | | array | | |
cruncep | PEcAn.data.atmosphere | | data.table | 8736 | 10 |
cruncep_landmask | PEcAn.data.atmosphere | | data.table | 259200 | 3 |
ebifarm | PEcAn.data.atmosphere | | data.table | 8390 | 10 |
landmask | PEcAn.data.atmosphere | | data.table | 18048 | 3 |
narr | PEcAn.data.atmosphere | | data.table | 8760 | 10 |
narr3h | PEcAn.data.atmosphere | | data.table | 8736 | 10 |
bcBathymetry | PBSmapping | Data: Bathymetry Spanning BC Coast | list | | |
nepacLL | PBSmapping | Data: Shorelines of the NE Pacific Ocean and of the World | PolySet | 75305 | 4 |
nepacLLhigh | PBSmapping | Data: Shorelines of the NE Pacific Ocean and of the World | PolySet | 192762 | 4 |
pythagoras | PBSmapping | Data: Pythagoras' Theorem Diagram PolySet | PolySet | 66 | 4 |
surveyData | PBSmapping | Data: Tow Information from Pacific Ocean Perch Survey | EventData | 674 | 9 |
towData | PBSmapping | Data: Tow Information from Longspine Thornyhead Survey | PolyData | 45 | 8 |
towTracks | PBSmapping | Data: Tow Track Polylines from Longspine Thornyhead Survey | PolySet | 3136 | 4 |
worldLL | PBSmapping | Data: Shorelines of the NE Pacific Ocean and of the World | PolySet | 30129 | 4 |
worldLLhigh | PBSmapping | Data: Shorelines of the NE Pacific Ocean and of the World | PolySet | 187101 | 4 |
corn_data | maize | Synthetic Corn Dataset for Corny Example | tbl_df | 300 | 3 |
Wenchuan | bgms | Post-traumatic stress disorder symptoms of Wenchuan earthquake survivors | matrix | 362 | 17 |
ZambiaAdm1 | surveyPrev | Admin 1 Polygon Map for Zambia. | SpatialPolygonsDataFrame | | |
ZambiaAdm2 | surveyPrev | Admin 2 Polygon Map for Zambia. | SpatialPolygonsDataFrame | | |
ZambiaPopWomen | surveyPrev | Population estimates for Women of age 15 to 49 in Zambia in 2018. | list | | |
surveyPrevIndicators | surveyPrev | Table of built-in indicators. | data.frame | 22 | 4 |
Data | yuima | Five minutes Log SPX prices | list | | |
MWK151 | yuima | Graybill - Methuselah Walk - PILO - ITRDB CA535 | zoo | | |
ArdecheStMartin | RtsEva | Simulated river discharge of the Ardeche river at Saint Martin d'Ardeche | data.frame | 102272 | 2 |
DanubeVienna | RtsEva | Simulated river discharge of the Danube river at Vienna | data.frame | 102272 | 2 |
EbroZaragoza | RtsEva | Simulated river discharge of the Ebro river at Zaragoza | data.frame | 102272 | 2 |
RhoneLyon | RtsEva | Simulated river discharge of the Rhone river at Lyon | data.frame | 102272 | 2 |
Jenkins2004_Table9 | PEcAn.allometry | | data.frame | 174 | 1 |
Table3_GTR-NE-319.v2 | PEcAn.allometry | | data.frame | 2642 | 1 |
allom.components | PEcAn.allometry | | data.frame | 41 | 3 |
exampledates | datefixR | Example dataset of dates in different formats | data.frame | 7 | 3 |
share | rarestR | Dataset for rarestR. | matrix | 3 | 142 |
Big5 | jmv | | data.frame | 500 | 5 |
ToothGrowth | jmv | | data.frame | 60 | 3 |
bugs | jmv | | data.frame | 93 | 8 |
iris | jmv | | data.frame | 150 | 5 |
invitrodb_dd | tcpl | Short descriptions of fields for different tables are stored in a data dictionary. | data.table | 44 | 3 |
load_data_columns | tcpl | Lists of column names returned from tcplLoadData invitrodb v4.1 (same as CCTE Bioactivity API version). | list | | |
mc_test | tcpl | List of lists containing queries sent to tcplQuery associated with each test case. Each list also contains the associated ids with each case. Only meant to be used with automated testing with mocking for mc data. | list | | |
mc_vignette | tcpl | List with multi-concentration data for the vignette | list | | |
mcdat | tcpl | A subset of ToxCast data showing changes in the activity of the intracellular estrogen receptor. | data.frame | 14183 | 10 |
sc_test | tcpl | List of lists containing queries sent to tcplQuery associated with each test case. Each list also contains the associated ids with each case. Only meant to be used with automated testing with mocking for sc data. | list | | |
sc_vignette | tcpl | List with single-concentration data for the vignette | list | | |
scdat | tcpl | A subset of ToxCast data showing changes in transcription factor activity for multiple targets. | data.frame | 320 | 10 |
test_api | tcpl | List containing ids used for different automated tests of tcpl integration with the CTX APIs, randomly selected from what is available via API. | list | | |
TCGA.organ | UCSCXenaShiny | TCGA: Organ Data | data.frame | 33 | 3 |
ccle_absolute | UCSCXenaShiny | ABSOLUTE Result of CCLE Database | tbl_df | 998 | 5 |
ccle_info | UCSCXenaShiny | Phenotype Info of CCLE Database | data.frame | 1046 | 14 |
ccle_info_fine | UCSCXenaShiny | Cleaned Phenotype Info of CCLE Database for grouping | tbl_df | 1046 | 5 |
pcawg_info | UCSCXenaShiny | Phenotype Info of PCAWG Database | tbl_df | 6231 | 27 |
pcawg_info_fine | UCSCXenaShiny | Cleaned Phenotype Info of PCAWG Database for grouping | tbl_df | 1523 | 5 |
pcawg_purity | UCSCXenaShiny | Purity Data of PCAWG | spec_tbl_df | 2778 | 6 |
tcga_clinical | UCSCXenaShiny | Toil Hub: TCGA Clinical Data | tbl_df | 12653 | 22 |
tcga_clinical_fine | UCSCXenaShiny | Toil Hub: Cleaned TCGA Clinical Data for grouping | tbl_df | 12591 | 8 |
tcga_genome_instability | UCSCXenaShiny | TCGA: Genome Instability Data | data.frame | 9997 | 6 |
tcga_gtex | UCSCXenaShiny | Toil Hub: Merged TCGA GTEx Selected Phenotype | data.frame | 18102 | 4 |
tcga_purity | UCSCXenaShiny | TCGA: Purity Data | tbl_df | 9364 | 7 |
tcga_subtypes | UCSCXenaShiny | TCGA Subtype Data | data.frame | 10469 | 10 |
tcga_surv | UCSCXenaShiny | Toil Hub: TCGA Survival Data | data.frame | 10496 | 9 |
toil_info | UCSCXenaShiny | Toil Hub: TCGA TARGET GTEX Selected Phenotype | data.frame | 19131 | 7 |
ensemble.output | PEcAn.uncertainty | | list | | |
ensemble.samples | PEcAn.uncertainty | | list | | |
sa.samples | PEcAn.uncertainty | | list | | |
sensitivity.output | PEcAn.uncertainty | | list | | |
settings | PEcAn.uncertainty | | list | | |
trait.samples | PEcAn.uncertainty | | list | | |
formats | pmeasyr | Table des formats | tbl_df | 26618 | 14 |
standard_vars | PEcAn.utils | Standardized variable names and units for PEcAn | data.frame | 117 | 12 |
trait.dictionary | PEcAn.utils | | data.frame | 101 | 4 |
BaFe2As2 | GeDS | Barium-Ferrum-Arsenide Powder Diffraction Data | data.frame | 1151 | 2 |
EWmortality | GeDS | Death counts in England and Wales | data.frame | 109 | 3 |
coalMining | GeDS | Coal Mining Disasters data | data.frame | 112 | 2 |
data.cqc01 | TAM | More Datasets and Examples (Similar to ConQuest Examples) | data.frame | 512 | 12 |
data.cqc02 | TAM | More Datasets and Examples (Similar to ConQuest Examples) | data.frame | 431 | 8 |
data.cqc03 | TAM | More Datasets and Examples (Similar to ConQuest Examples) | data.frame | 11200 | 4 |
data.cqc04 | TAM | More Datasets and Examples (Similar to ConQuest Examples) | data.frame | 1452 | 8 |
data.cqc05 | TAM | More Datasets and Examples (Similar to ConQuest Examples) | data.frame | 1500 | 160 |
data.ctest1 | TAM | Some C-Test Datasets | data.frame | 1675 | 42 |
data.ctest2 | TAM | Some C-Test Datasets | list | | |
data.ex08 | TAM | Datasets 'data.ex' in 'TAM' Package | list | | |
data.ex10 | TAM | Datasets 'data.ex' in 'TAM' Package | data.frame | 675 | 7 |
data.ex11 | TAM | Datasets 'data.ex' in 'TAM' Package | data.frame | 3400 | 13 |
data.ex12 | TAM | Datasets 'data.ex' in 'TAM' Package | matrix | 100 | 10 |
data.ex14 | TAM | Datasets 'data.ex' in 'TAM' Package | data.frame | 1110 | 11 |
data.ex15 | TAM | Datasets 'data.ex' in 'TAM' Package | data.frame | 2155 | 182 |
data.ex16 | TAM | Datasets 'data.ex' in 'TAM' Package | data.frame | 3235 | 25 |
data.ex17 | TAM | Datasets 'data.ex' in 'TAM' Package | data.frame | 3235 | 15 |
data.exJ03 | TAM | Datasets 'data.ex' in 'TAM' Package | list | | |
data.fims.Aus.Jpn.raw | TAM | Dataset FIMS Study with Responses of Australian and Japanese Students | data.frame | 6371 | 16 |
data.fims.Aus.Jpn.scored | TAM | Dataset FIMS Study with Responses of Australian and Japanese Students | data.frame | 6371 | 16 |
data.geiser | TAM | Dataset from Geiser et al. (2006) | data.frame | 519 | 24 |
data.gpcm | TAM | Dataset with Ordered Indicators | data.frame | 392 | 3 |
data.janssen | TAM | Dataset from Janssen and Geiser (2010) | data.frame | 346 | 8 |
data.janssen2 | TAM | Dataset from Janssen and Geiser (2010) | data.frame | 346 | 20 |
data.mc | TAM | Dataset with Raw and Scored Responses from Multiple Choice Items | list | | |
data.numeracy | TAM | Dataset Numeracy | list | | |
data.sim.facets | TAM | Simulated Multifaceted Data | data.frame | 100 | 3 |
data.sim.mfr | TAM | Simulated Multifaceted Data | matrix | 100 | |
data.sim.rasch | TAM | Simulated Rasch data | matrix | 2000 | 40 |
data.sim.rasch.missing | TAM | Simulated Rasch data | matrix | 2000 | 40 |
data.sim.rasch.pweights | TAM | Simulated Rasch data | matrix | 1000 | 40 |
data.timssAusTwn | TAM | Dataset TIMSS 2011 of Australian and Taiwanese Students | data.frame | 1773 | 14 |
data.timssAusTwn.scored | TAM | Dataset TIMSS 2011 of Australian and Taiwanese Students | data.frame | 1769 | 14 |
emedyd | rcarbon | Radiocarbon dates for the Eastern Mediterranean around the Younger Dryas | data.frame | 1915 | 10 |
euroevol | rcarbon | Radiocarbon dates from the EUROEVOL database | data.frame | 14053 | 9 |
ewdates | rcarbon | Subset of EUROEVOL radiocarbon dates from Great Britain | data.frame | 2327 | 9 |
ewowin | rcarbon | Polygonal window of England and Wales | owin | | |
patternsWithFormula | DrugUtilisation | Patterns valid to compute daily dose with the associated formula. | tbl_df | 41 | 9 |
countData | SurfR | countData | matrix | 2500 | 4 |
enrichedList | SurfR | enrichedList | list | | |
ind_deg | SurfR | ind_deg | list | | |
metadata | SurfR | metadata | data.frame | 4 | 3 |
mu_est_long | nichetools | A 'data.frame' containing posterior estimates of mu | tbl_df | 8000 | 7 |
niw_fish_post | nichetools | A 'list' of the posterior estimates of mu and Sigma from '{nicheROVER}' | list | | |
over_stat | nichetools | A 'data.frame' containing the estimates of percentage of overlap among groups | array | | |
post_sam_siber | nichetools | A 'list' of the posterior estimates of mu and Sigma from '{SIBER}' | list | | |
sigma_est_wide | nichetools | A 'data.frame' containing posterior estimates of Sigma | tbl_df | 8000 | 6 |
germany_covid19_hosp | epinowcast | Hospitalisations in Germany by date of report and reference | data.table | 1536885 | 5 |
cog_2023 | happign | COG 2023 | data.frame | 34990 | 2 |
cookfarm | CAST | Cookfarm soil logger data | data.frame | 128545 | 17 |
splotdata | CAST | sPlotOpen Data of Species Richness | sf | 703 | 17 |
auckland_queries | text2sdg | SDG queries of the University of Auckland | tbl_df | 16 | 4 |
aurora_queries | text2sdg | SDG queries of the Aurora Universities Network | tbl_df | 373 | 6 |
elsevier_queries | text2sdg | SDG queries of Elsevier | tbl_df | 16 | 4 |
projects | text2sdg | Descriptions of research projects | character | | |
sdgo_queries | text2sdg | SDG Ontology by OSDG | tbl_df | 4122 | 5 |
sdsn_queries | text2sdg | SDG keywords by SDSN | tbl_df | 847 | 5 |
siris_queries | text2sdg | SDG queries of SIRIS Academic | tbl_df | 3445 | 6 |
breast_cancer | QuadratiK | Breast Cancer Wisconsin (Diagnostic) | data.frame | 569 | 31 |
wine | QuadratiK | Wine data set | data.frame | 178 | 14 |
wireless | QuadratiK | Wireless Indoor Localization | data.frame | 2000 | 8 |
PlethMorph | RRPP | Plethodon comparative morphological data | rrpp.data.frame | | |
Pupfish | RRPP | Landmarks on pupfish | rrpp.data.frame | | |
PupfishHeads | RRPP | Landmarks on pupfish heads | rrpp.data.frame | | |
fishy | RRPP | Simulated fish data for measurement error analysis | list | | |
motionpaths | RRPP | Simulated motion paths | list | | |
epilepsy | brms | Epileptic seizure counts | data.frame | 236 | 9 |
inhaler | brms | Clarity of inhaler instructions | data.frame | 572 | 5 |
kidney | brms | Infections in kidney patients | data.frame | 76 | 7 |
loss | brms | Cumulative Insurance Loss Payments | data.frame | 55 | 4 |
data_altruism_happiness | esci | Altruism Happiness - Ch12 - from Brethel-Haurwitz and Marsh (2014) | data.frame | 50 | 6 |
data_anchor_estimate_ma | esci | Anchor Estimate ma - Ch9 - Many Labs replications of Jacowitz and Kahneman (1995) | data.frame | 30 | 9 |
data_basol_badnews | esci | Basol badnews - Ch07 - from Basol et al. (2020) | data.frame | 198 | 3 |
data_bem_psychic | esci | Bem Psychic - Ch13 - from Bem and Honorton (1994) | data.frame | 10 | 5 |
data_bodywellf | esci | BodyWellF - Ch12 - Body Satisfaction and Well-being data for females from Figure 11.24 right panel | data.frame | 59 | 2 |
data_bodywellfm | esci | BodyWellFM - Ch12 - Body Satisfaction and Well-being data from Figure 11.1 | data.frame | 106 | 2 |
data_bodywellm | esci | BodyWellM - Ch12 - Body Satisfaction and Well-being data for males from Figure 11.24 left panel | data.frame | 47 | 2 |
data_campus_involvement | esci | Campus Involvement - Ch11 - for End-of-Chapter Exercise 11.7 | data.frame | 113 | 6 |
data_chap_8_paired_ex_8.18 | esci | _Fictitious_ data from an unrealistically small HEAT study comparing scores for a single group of students before and after a workshop on climate change. | data.frame | 8 | 2 |
data_clean_moral | esci | Clean moral - Ch07 - from Schnall et al. (2008), Study 1, and Johnson et al. (2014) | data.frame | 208 | 4 |
data_college_survey_1 | esci | College survey 1 - Ch03 - for End-of-Chapter Exercise 3.3 | data.frame | 243 | 23 |
data_college_survey_2 | esci | College survey 2 - Ch05 - for End-of-Chapter Exercise 5.4 | data.frame | 138 | 17 |
data_damischrcj | esci | DamischRCJ - Ch9 - from 6 Damisch studies, and Calin-Jageman and Caldwell (2014) | data.frame | 8 | 5 |
data_effronraj_fakenews | esci | EffronRaj fakenews - Ch8 - from Effron and Raj (2020) | data.frame | 138 | 5 |
data_emotion_heartrate | esci | Emotion heartrate - Ch8 - from Lakens (2013) | data.frame | 68 | 3 |
data_exam_scores | esci | Exam Scores - Ch11 - for End-of-Chapter Exercise 11.2 | data.frame | 9 | 3 |
data_flag_priming_ma | esci | Flag Priming ma - Ch9 - Many Labs replications of Carter et al. (2011) | data.frame | 25 | 7 |
data_gender_math_iat | esci | Gender math IAT - Ch07 - Ithaca and SDSU replications of Nosek et al. (2002) | data.frame | 155 | 4 |
data_gender_math_iat_ma | esci | Gender math IAT ma - Ch9 - Many Labs replications of Nosek et al. (2002) | data.frame | 30 | 9 |
data_halagappa | esci | Halagappa - Ch14 - from Halagappa et al. (2007) | data.frame | 6 | 4 |
data_home_prices | esci | Home Prices - Ch12 - for End-of-Chapter Exercise 12.2 | data.frame | 300 | 8 |
data_kardas_expt_3 | esci | Kardas Expt 3 - Ch07 - from Kardas and O'Brien (2018), Experiment 3 | data.frame | 100 | 3 |
data_kardas_expt_4 | esci | Kardas Expt 4 - Ch07 - from Kardas and O'Brien (2018), Experiment 4 | data.frame | 270 | 4 |
data_labels_flavor | esci | Labels flavor - Ch8 - from Floretta-Schiller et al. (2015) | data.frame | 51 | 6 |
data_latimier_3groups | esci | Latimier 3Groups - Ch14 - 3 groups in Latimier et al. (2019) | data.frame | 285 | 3 |
data_latimier_prequiz | esci | Latimier Prequiz - Ch03 - Prequiz group in Latimier et al. (2019) | data.frame | 95 | 3 |
data_latimier_quiz | esci | Latimier Quiz - Ch03 - Quiz group in Latimier et al. (2019) | data.frame | 95 | 3 |
data_latimier_quiz_prequiz | esci | Latimier Quiz Prequiz - Ch07 - Quiz and Prequiz groups in Latimier et al. (2019) | data.frame | 190 | 3 |
data_latimier_reread | esci | Latimier Reread - Ch03 - Reread group in Latimier et al. (2019) | data.frame | 95 | 3 |
data_latimier_reread_prequiz | esci | Latimier Reread Prequiz - Ch07 - Reread and Prequiz groups in Latimier et al. (2019) | data.frame | 190 | 3 |
data_latimier_reread_quiz | esci | Latimier Reread Quiz - Ch07 - Reread and Quiz groups in Latimier et al. (2019) | data.frame | 190 | 3 |
data_macnamara_r_ma | esci | Macnamara r ma - Ch11 - from Macnamara et al. (2014) | data.frame | 16 | 4 |
data_mccabemichael_brain | esci | McCabeMichael brain - Ch9 - from Michael et al. (2013) | data.frame | 10 | 9 |
data_mccabemichael_brain2 | esci | McCabeMichael brain2 - Ch9 - from Michael et al. (2013) | data.frame | 12 | 9 |
data_meditationbrain | esci | MeditationBrain - Ch15 - from Holzel et al. (2011) | data.frame | 33 | 7 |
data_organicmoral | esci | OrganicMoral - Ch14 - from Eskine (2013) | data.frame | 106 | 6 |
data_penlaptop1 | esci | % transcription scores from pen and laptop group of Meuller et al., 2014 | data.frame | 65 | 2 |
data_powerperformance_ma | esci | PowerPerformance ma - Ch9 - from Burgmer and Englich (2012), and Cusack et al. (2015) | data.frame | 8 | 12 |
data_rattanmotivation | esci | RattanMotivation - Ch14 - from Rattan et al. (2012) | data.frame | 54 | 2 |
data_religionsharing | esci | ReligionSharing - Ch14 - for End-of-Chapter Exercise 14.3 | data.frame | 3 | 4 |
data_religious_belief | esci | Religious belief - Ch03 - for End-of-Chapter Exercise 3.5 | data.frame | 213 | 3 |
data_selfexplain | esci | SelfExplain - Ch15 - from McEldoon et al. (2013) | data.frame | 52 | 4 |
data_simmonscredibility | esci | SimmonsCredibility - Ch14 - from Simmons and Nelson (2020) | data.frame | 3 | 4 |
data_sleep_beauty | esci | Sleep Beauty - Ch11 - for End-of-Chapter Exercise 11.6 | data.frame | 70 | 2 |
data_smithrecall | esci | SmithRecall - Ch15 - from Smith et al. (2016) | data.frame | 120 | 6 |
data_stickgold | esci | Stickgold - Ch06 - from Stickgold et al. (2000) | data.frame | 11 | 3 |
data_studystrategies | esci | StudyStrategies - Ch14 - from O'Reilly et al. (1998) | data.frame | 3 | 10 |
data_thomason_1 | esci | Thomason 1 - Ch11 - from Thomason 1 | data.frame | 12 | 3 |
data_videogameaggression | esci | VideogameAggression - Ch15 - from Hilgard (2015) | data.frame | 223 | 3 |
BirthDeath | hmer | Birth-Death Model Results | list | | |
SIREmulators | hmer | Sample Emulators | list | | |
SIRImplausibility | hmer | Sample Implausibility Data | data.frame | 1000 | 7 |
SIRMultiWaveData | hmer | Sample Multi-wave Results | list | | |
SIRMultiWaveEmulators | hmer | Sample Multi-wave Emulators | list | | |
SIRSample | hmer | Sample SIR data | list | | |
SIR_stochastic | hmer | Stochastic SIR Data | list | | |
problem_data | hmer | Data for an interesting emulation problem | list | | |
aboutrsq | datana | About the R-Squared statistics: the Anscombe quartet dataset | data.frame | 11 | 6 |
aboutrsq2 | datana | Sobre el estadรญstico R2: los datos del cuarteto de Anscombe | data.frame | 11 | 6 |
airnyc | datana | Airquality data in New York city. | data.frame | 153 | 6 |
airnyc2 | datana | Calidad del aire en la ciudad de Nueva York. | data.frame | 153 | 6 |
annualppCities | datana | Time series of annual precipitations in cities of Chile. | data.frame | 340 | 3 |
annualppCities2 | datana | Serie de tiempo de precipitaciones anuales en Chile. | data.frame | 340 | 3 |
araucaria | datana | Contains plot-level variables in Araucaria araucana forests in southern Chile. | data.frame | 74 | 12 |
araucaria2 | datana | Variables a nivel de parcela para bosques de Araucaria araucana el sur de Chile. | data.frame | 74 | 12 |
baiTreelines | datana | Annual basal area increment for four tree species. | data.frame | 157 | 7 |
baiTreelines2 | datana | Incremento anual en area basal de cuatro especies arboreas. | data.frame | 157 | 7 |
bears | datana | Age and physical measurement data for wild bears | data.frame | 143 | 12 |
bears2 | datana | Edad y caracterรญsticas biomรฉtricas de osos salvajes | data.frame | 143 | 12 |
bearsDepu | datana | Age and physical measurement data for wild bears (without missing values) | data.frame | 82 | 12 |
bearsDepu2 | datana | Edad y caracterรญsticas biomรฉtricas de osos salvajes (sin datos faltantes) | data.frame | 82 | 12 |
beetles | datana | Population density growth of beetles | data.frame | 240 | 4 |
beetles2 | datana | Crecimiento poblacional de escarabajos | data.frame | 240 | 4 |
biomass | datana | Contains tree-level biomass data for several species in Canada. | data.frame | 1013 | 8 |
biomass2 | datana | Biomasa a nivel de รกrbol para especies arboreas de Canada. | data.frame | 1013 | 8 |
carbohydrateTreelines | datana | Carbohydrates concentrations of tree species. | data.frame | 863 | 16 |
chicksw | datana | Chicken growth data. | data.frame | 578 | 4 |
corkoak | datana | Tree-level cork biomass data for Oak trees in Portugal | data.frame | 203 | 10 |
corkoak2 | datana | Datos de biomasa de corcho en รกrboles de Encino en Portugal | data.frame | 203 | 10 |
crown | datana | Tree crown radii | data.frame | 30 | 10 |
crown2 | datana | Radios de copa de รกrboles | data.frame | 30 | 10 |
deadForestCA | datana | Data contains climatic, forest structure and forest mortality variable | data.frame | 11763 | 20 |
deadForestCA2 | datana | Los datos contienen variables climaticas, de estructura forestal y de mortalidad forestal. | data.frame | 11763 | 20 |
deadLianas | datana | This dataset has 43 columns and 4247 rows. Each row corresponds to an epiphyte individual located on the reliable sections of the host trees | data.frame | 4247 | 52 |
deadLianas2 | datana | Este conjunto de datos tiene 43 columnas y 4247 filas. Cada fila corresponde a un individuo epifito ubicado en el secciones confiables de los รกrboles hospedantes | data.frame | 4247 | 52 |
demograph | datana | Contains information of demography of species. | data.frame | 61 | 15 |
election | datana | Presidential election data of Florida (USA) in 2000. | data.frame | 67 | 3 |
election2 | datana | Elecciรณn presidencial en el estado de Florida (USA) en el 2000. | data.frame | 67 | 3 |
eucaleaf | datana | Leaf measurements for Eucalyptus nitens trees in Tasmania, Australia. | data.frame | 501 | 6 |
eucaleaf2 | datana | Mediciones foliares para รกrboles de Eucalyptus nitens en Tasmania, Australia. | data.frame | 501 | 6 |
eucaleafAll | datana | Leaf measurements (all, n=744) for Eucalyptus nitens trees in Tasmania, Australia. | data.frame | 744 | 6 |
eucaleafAll2 | datana | Mediciones foliares (todas, n=744) para รกrboles de Eucalyptus nitens en Tasmania, Australia. | data.frame | 744 | 6 |
eucaplot | datana | Data from a Eucalyptus globulus plantation near Gorbea, Region de La Araucania, Chile. | data.frame | 15 | 5 |
eucaplot2 | datana | รrboles dentro de parcelas de muestreo en una plantaciรณn de Eucalyptus globulus, Chile. | data.frame | 15 | 5 |
fertiliza | datana | Fertilization experiment data. | data.frame | 15 | 2 |
fertiliza2 | datana | Datos a nivel de parcela de un experimento de fertilizaciรณn | data.frame | 15 | 2 |
ficdiamgr | datana | Diameter growth of trees | data.frame | 35 | 5 |
ficdiamgr2 | datana | Crecimiento diametral de รกrboles | data.frame | 35 | 5 |
fishgrowth | datana | Data on fish growth. | data.frame | 439 | 3 |
fishgrowth2 | datana | Crecimiento de peces | data.frame | 439 | 3 |
floraChile | datana | Flora of Chile. | data.frame | 3787 | 45 |
floraChile2 | datana | Flora de Chile. | data.frame | 3787 | 45 |
football | datana | Anaerobic potential of soccer players. | data.frame | 23 | 14 |
football2 | datana | Potencia anaerobica de jugadores de football. | data.frame | 23 | 14 |
forestFire | datana | Data of forest fire occurrence | data.frame | 822 | 25 |
forestFire2 | datana | Datos de ocurrencia de incendios forestales | data.frame | 822 | 25 |
forestHawaii | datana | Contains information of forest plots across the Hawaiian archipelago. | data.frame | 43590 | 18 |
hawaii | datana | Diameter growth increments of a tropical tree species in Hawaii | data.frame | 63 | 8 |
hawaii2 | datana | Incremento corriente anual en diรกmetro de una especie tropical en Hawaii | data.frame | 63 | 8 |
hgrdfir | datana | Tree height growth of Douglas-fir sample trees in the Northwest of the United States | data.frame | 148 | 7 |
hgrdfir2 | datana | Crecimiento en altura de una muestra de รกrboles en los Estados Unidos | data.frame | 148 | 7 |
idahohd | datana | Tree height-diameter data from Idaho (USA) | data.frame | 372 | 6 |
idahohd2 | datana | Altura-diรกmetro de รกrboles en el estado de Idaho (USA) | data.frame | 372 | 6 |
invasivesRCI | datana | Contains regeneration microsite data in Robinson Crusoe Island forest | data.frame | 51 | 10 |
landCoverSantiago | datana | Land-cover, environmental and sociodemographic data for the 34 municipalities composing the Greater Santiago area, Santiago, Chile. | data.frame | 34 | 14 |
landCoverSantiago2 | datana | Cobertura territorial, ambiental y sociodemografica de los 34 municipios que componen el area del Gran Santiago, Santiago, Chile.. | data.frame | 34 | 14 |
lleuque | datana | Contains species composition data of Prumnopitys andina (Lleuque) forests | data.frame | 26 | 6 |
pinaster | datana | Tree volume for Pinus pinaster in the Baixo-Mino, Galicia, Spain. | data.frame | 85 | 8 |
pinaster2 | datana | Volumen individual de รกrboles de Pinus pinaster en Galicia, Espaรฑa. | data.frame | 85 | 8 |
pinusContorta | datana | Contains spatial location of Pinus contorta trees in sample plots. | data.frame | 2552 | 8 |
pinusContorta2 | datana | Ubicaciรณn espacial de รกrboles de Pinus contorta en parcela de muestreo | data.frame | 2552 | 8 |
pinusSpp | datana | Tree-level variables of several sample plots of invasive Pinus spp in Chile. | data.frame | 1215 | 11 |
pinusSpp2 | datana | Variables a nivel de รกrbol en parcelas de muestreo de Pinus spp en Chile. | data.frame | 1215 | 11 |
plantsHawaii | datana | Maximum plant size in the Hawaiian archipelago. | data.frame | 58 | 6 |
presenceIce | datana | Presence or absence of sea ice from logbook records of annual cruises | data.frame | 52717 | 9 |
presidentChile | datana | 2021 presidential election in Chile. | data.frame | 184360 | 15 |
presidentChile2 | datana | Eleccion presidencial del 2021 en Chile. | data.frame | 184360 | 15 |
primary | datana | 2021 primary election for the president of Chile | data.frame | 130110 | 16 |
primary2 | datana | Elecciรณn primaria para la presidencia de Chile | data.frame | 130110 | 16 |
pspLlancahue | datana | Tree locations for a sample plot in the Llancahue experimental forest | data.frame | 1218 | 5 |
pspLlancahue2 | datana | Ubicaciรณn cartesiana de รกrboles en el bosque de Llancahue | data.frame | 1218 | 5 |
pspRuca | datana | Tree spatial coordinates in the Rucamanque forest | data.frame | 661 | 6 |
pspRuca2 | datana | Ubicaciรณn espacial de รกrboles en el bosque de Rucamanque | data.frame | 661 | 6 |
ptaeda | datana | Height growth of Pinus taeda (Loblolly pine) trees | data.frame | 84 | 3 |
ptaeda2 | datana | Crecimiento en altura de Pinus taeda | data.frame | 84 | 3 |
radiatapl | datana | Sampling plots data from a Pinus radiata plantation near Capitan Pastene, Region de La Araucania, Chile. | data.frame | 125 | 4 |
radiatapl2 | datana | Datos a nivel de รกrbol de parcelas de muestreo en plantaciones de Pinus radiata | data.frame | 125 | 4 |
raulihg | datana | Height growth of Nothofagus alpina trees in Chile. | data.frame | 524 | 4 |
raulihg2 | datana | Crecimiento en altura de รกrboles de Nothofagus alpina. | data.frame | 524 | 4 |
regNothofagus | datana | Contains information about regeneration of Nothofagus seedlings. | data.frame | 442 | 15 |
simula | datana | Simulated yield of forestry plantations of exotic species in Chile. | data.frame | 63 | 11 |
slashpine | datana | Biomass dataset | data.frame | 40 | 9 |
slashpine2 | datana | Biomasa | data.frame | 40 | 9 |
sludge | datana | Sludge data are at different cities, with a value of concentration zinc. | data.frame | 36 | 4 |
snaspeChile | datana | On the National System of State Protected Wild Areas (SNASPE) of Chile. | data.frame | 118 | 9 |
snaspeChile2 | datana | Sistema nacional de areas protegidas del estado (SNASPE) de Chile | data.frame | 118 | 9 |
soiltreat | datana | Soil treatment experiment in tree seedlings | data.frame | 33 | 4 |
soiltreat2 | datana | Tratamientos del suelo en el crecimiento de plantulas. | data.frame | 33 | 4 |
spatAustria | datana | Tree locations for several plots of Norway spruce in Austria | data.frame | 1927 | 7 |
speciesList | datana | Names and other information of plant species (mainly trees) | data.frame | 63 | 32 |
sppAbundance | datana | Contains information of abundance of plant species in the central-southern Andes of Chile. | data.frame | 49 | 6 |
sppTraits | datana | Contains information of functional traits of species. | data.frame | 48 | 17 |
standLleuque | datana | Plot-level data with variables from Andean Prumnopitys forests | data.frame | 24 | 7 |
standLleuque2 | datana | Datos con variables a nivel de parcela de bosques de Prumnopitys andina | data.frame | 24 | 7 |
trailCameraTrap | datana | Contains information of Camera trap data on medium to large terrestrial mammals collected at 54 camera stations in Ruaha National Park, southern Tanzania. | data.frame | 14604 | 6 |
traits | datana | Functional traits of vegetative species in Chile. | data.frame | 32 | 5 |
traits2 | datana | Rasgos funcionales para algunas especies vegetales de Chile. | data.frame | 32 | 5 |
treegr | datana | Diameter and height growth of Grand-fir (Abies grandis) sample trees | data.frame | 542 | 7 |
treegr2 | datana | Crecimiento en diรกmetro y altura de รกrboles muestras de Grand-fir (Abies grandis) | data.frame | 542 | 7 |
treelistinve | datana | Tree-list data in a forest inventory. | data.frame | 343 | 6 |
treelistinve2 | datana | Lista de รกrboles en un inventario forestal. | data.frame | 343 | 6 |
treevol | datana | Diameter, height and volume for Black Cherry Trees | data.frame | 31 | 3 |
treevol2 | datana | Volumen, altura, y diรกmetro para รกrboles de Black Cherry | data.frame | 31 | 3 |
treevolroble | datana | Tree volume of roble (Nothofagus obliqua) in the Rucamanque forest | data.frame | 106 | 5 |
treevolroble2 | datana | Volumen a nivel de รกrbol para roble (Nothofagus obliqua) especie en el bosque de Rucamanque | data.frame | 106 | 6 |
treevolruca | datana | Tree volume by species in the Rucamanque forest | data.frame | 382 | 6 |
treevolruca2 | datana | Volumen a nivel de รกrbol en el bosque de Rucamanque | data.frame | 382 | 6 |
kobestatistics | mse | Kobe statistics | list | | |
oem | mse | S4 class 'FLmse' | FLoem | | |
oem | mse | S4 class 'FLmse' | FLoem | | |
om | mse | S4 class 'FLmse' | FLom | | |
om | mse | S4 class 'FLmse' | FLom | | |
statistics | mse | Example set of performance statistics | list | | |
kid | kyotil | Dataset from Cowling et al. | data.frame | 736 | 10 |
intcal20 | nimbleCarbon | IntCal20 radiocarbon age calibration curve for the Northern hemisphere. | data.frame | 9501 | 5 |
marine20 | nimbleCarbon | Marine20 radiocarbon age calibration curve. | data.frame | 5501 | 5 |
shcal20 | nimbleCarbon | IntCal20 radiocarbon age calibration curve for the Southern hemisphere. | data.frame | 9501 | 5 |
diamonds | ggplot2 | Prices of over 50,000 round cut diamonds | tbl_df | 53940 | 10 |
economics | ggplot2 | US economic time series | spec_tbl_df | 574 | 6 |
economics_long | ggplot2 | US economic time series | tbl_df | 2870 | 4 |
faithfuld | ggplot2 | 2d density estimate of Old Faithful data | tbl_df | 5625 | 3 |
luv_colours | ggplot2 | 'colors()' in Luv space | data.frame | 657 | 4 |
midwest | ggplot2 | Midwest demographics | tbl_df | 437 | 28 |
mpg | ggplot2 | Fuel economy data from 1999 to 2008 for 38 popular models of cars | tbl_df | 234 | 11 |
msleep | ggplot2 | An updated and expanded version of the mammals sleep dataset | tbl_df | 83 | 11 |
presidential | ggplot2 | Terms of 12 presidents from Eisenhower to Trump | tbl_df | 12 | 4 |
seals | ggplot2 | Vector field of seal movements | tbl_df | 1155 | 4 |
txhousing | ggplot2 | Housing sales in TX | tbl_df | 8602 | 9 |
AF92Lt | lifecontingencies | Uk AM AF 92 life tables | lifetable | | |
AM92Lt | lifecontingencies | Uk AM AF 92 life tables | lifetable | | |
SoAISTdata | lifecontingencies | SoA illustrative service table | data.frame | 41 | 6 |
de_angelis_di_falco | lifecontingencies | Italian Health Insurance Data | list | | |
demoCanada | lifecontingencies | Canada Mortality Rates for UP94 Series | data.frame | 120 | 7 |
demoChina | lifecontingencies | China Mortality Rates for life table construction | data.frame | 106 | 8 |
demoFrance | lifecontingencies | French population life tables | data.frame | 113 | 5 |
demoGermany | lifecontingencies | German population life tables | data.frame | 112 | 3 |
demoIta | lifecontingencies | Italian population life tables for males and females | data.frame | 121 | 18 |
demoJapan | lifecontingencies | Japan Mortality Rates for life table construction | data.frame | 110 | 3 |
demoUk | lifecontingencies | UK life tables | data.frame | 74 | 3 |
demoUsa | lifecontingencies | United States Social Security life tables | data.frame | 114 | 7 |
soa08 | lifecontingencies | Society of Actuaries Illustrative Life Table object. | lifetable | | |
soa08Act | lifecontingencies | Society of Actuaries Illustrative Life Table with interest rate at 6 | actuarialtable | | |
soaLt | lifecontingencies | Society of Actuaries life table | data.frame | 111 | 2 |
name_conversions | VicmapR | Name conversions between old and new geoserver | tbl_df | 630 | 5 |
BaalObject | BaalChIP | BaalObject example dataset | BaalChIP | | |
ENCODEexample | BaalChIP | ENCODEexample example dataset | BaalChIP | | |
FAIREexample | BaalChIP | FAIREexample example dataset | BaalChIP | | |
UniqueMappability50bp_hg19 | BaalChIP | Genomic regions of unique mappability | GRanges | | |
blacklist_hg19 | BaalChIP | Blacklisted genomic regions | GRanges | | |
pickrell2011cov1_hg19 | BaalChIP | Genomic regions of collapsed repeats | GRanges | | |
beta | methyLImp2 | A subset of GSE199057 dataset for vignette demonstration | matrix | 24 | 6064 |
beta_meta | methyLImp2 | Metadata information for GSE199057 dataset for vignette demonstration | data.frame | 24 | 42 |
custom_anno_example | methyLImp2 | An example of how custom (user provided) annotation data frame should look like | data.frame | 5 | 2 |
cell_data | cicero | Metadata for example cells in cicero_data | data.frame | 200 | 2 |
cicero_data | cicero | Example single-cell chromatin accessibility data | data.frame | 35137 | 3 |
gene_annotation_sample | cicero | Example gene annotation information | data.frame | 15129 | 8 |
human.hg19.genome | cicero | Chromosome lengths from human genome hg19 | data.frame | 93 | 2 |
alos_palsar_band_mapping | rsi | ALOS PALSAR band mapping | list | | |
dem_band_mapping | rsi | Landsat band mapping | list | | |
landsat_band_mapping | rsi | Landsat band mapping | list | | |
sentinel1_band_mapping | rsi | Sentinel-1 band mapping | list | | |
sentinel2_band_mapping | rsi | Sentinel-2 band mapping | list | | |
WarblerG | pedtricks | Seychelles Warbler Genotypes | data.frame | 307 | 29 |
gryphons | pedtricks | Example dataset for pedtricks examples and tutorial | data.frame | 4918 | 9 |
nzmort | poputils | Mortality Data for New Zealand | tbl_df | 84 | 6 |
nzmort_rvec | poputils | Mortality Data and Probabilistic Rates for New Zealand | tbl_df | 84 | 4 |
west_lifetab | poputils | Coale-Demeny West Model Life Tables | tbl_df | 1050 | 10 |
data1 | bliss | a list of data | list | | |
param1 | bliss | A list of param for bliss model | list | | |
res_bliss1 | bliss | A result of the BliSS method | bliss | | |
toy | akiFlagger | Toy dataset | data.table | 1078 | 6 |
AA2DACOR | protr | 2D Autocorrelations Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 92 |
AA3DMoRSE | protr | 3D-MoRSE Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 160 |
AAACF | protr | Atom-Centred Fragments Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 6 |
AABLOSUM100 | protr | BLOSUM100 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AABLOSUM45 | protr | BLOSUM45 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AABLOSUM50 | protr | BLOSUM50 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AABLOSUM62 | protr | BLOSUM62 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AABLOSUM80 | protr | BLOSUM80 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AABurden | protr | Burden Eigenvalues Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 62 |
AACPSA | protr | CPSA Descriptors for 20 Amino Acids calculated by Discovery Studio | data.frame | 20 | 41 |
AAConn | protr | Connectivity Indices Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 33 |
AAConst | protr | Constitutional Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 23 |
AADescAll | protr | All 2D Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 1171 |
AAEdgeAdj | protr | Edge Adjacency Indices Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 97 |
AAEigIdx | protr | Eigenvalue-Based Indices Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 44 |
AAFGC | protr | Functional Group Counts Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 5 |
AAGETAWAY | protr | GETAWAY Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 194 |
AAGeom | protr | Geometrical Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 41 |
AAInfo | protr | Information Indices Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 47 |
AAMOE2D | protr | 2D Descriptors for 20 Amino Acids calculated by MOE 2011.10 | data.frame | 20 | 148 |
AAMOE3D | protr | 3D Descriptors for 20 Amino Acids calculated by MOE 2011.10 | data.frame | 20 | 143 |
AAMetaInfo | protr | Meta Information for the 20 Amino Acids | data.frame | 20 | 6 |
AAMolProp | protr | Molecular Properties Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 12 |
AAPAM120 | protr | PAM120 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AAPAM250 | protr | PAM250 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AAPAM30 | protr | PAM30 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AAPAM40 | protr | PAM40 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AAPAM70 | protr | PAM70 Matrix for 20 Amino Acids | matrix | 20 | 20 |
AARDF | protr | RDF Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 82 |
AARandic | protr | Randic Molecular Profiles Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 41 |
AATopo | protr | Topological Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 78 |
AATopoChg | protr | Topological Charge Indices Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 15 |
AAWHIM | protr | WHIM Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 99 |
AAWalk | protr | Walk and Path Counts Descriptors for 20 Amino Acids calculated by Dragon | data.frame | 20 | 40 |
AAindex | protr | AAindex Data of 544 Physicochemical and Biological Properties for 20 Amino Acids | data.frame | 544 | 26 |
flea | tourr | Flea beatle measurements | data.frame | 74 | 7 |
flea_raw | tourr | Flea beatle measurements | data.frame | 74 | 7 |
laser | tourr | Turnable laser measurements from Bellcore | data.frame | 64 | 4 |
olive | tourr | Olive oil samples from Italy | data.frame | 572 | 10 |
ozone | tourr | Monthly ozone measurements over Central America | array | | |
places | tourr | Ratings of different locations across North America | data.frame | 329 | 14 |
ratcns | tourr | Rat CNS Gene Expression | data.frame | 112 | 11 |
t1 | tourr | Saved history of guided tour with holes | history_array | | |
tao | tourr | Tropical Atmosphere Ocean data | data.frame | 736 | 8 |
sim | MixRF | Simulated data list | list | | |
gdal_web_sources | gdalwebsrv | | tbl_df | 11 | 2 |
web_sources | gdalwebsrv | | tbl_df | 12 | 2 |
gt1m_sample | pawacc | GT1M accelerometer file | accfile | | |
gt3x_sample | pawacc | GT3X accelerometer file | accfile | | |
BanxicoCatalog | banxicoR | Catalog of some ID's | data.frame | 133 | 9 |
rats | nlmm | Growth curves | data.frame | 135 | 4 |
demo_data | lactater | Demo data | tbl_df | 8 | 5 |
X | MixedIndTests | AR(1) Poisson with parameters | numeric | | |
Xbin | MixedIndTests | Bernoulli sequence | numeric | | |
Y | MixedIndTests | VAR(1) Poisson with parameters | matrix | 100 | |
horseshoecrabs | MixedIndTests | Horseshoecrabs dataset | data.frame | 173 | 5 |
lamb | MixedIndTests | Fetal lamb dataset | integer | | |
compas | fairadapt | COMPAS dataset. | data.frame | 7214 | 9 |
gov_census | fairadapt | Census information of US government employees. | data.table | 204309 | 17 |
uni_admission | fairadapt | University admission data of 1,000 students. | data.frame | 1000 | 4 |
flood | jointPm | Example data of flood levels and dependence strength between extreme rainfall and extreme storm tides from a coastal catchment | list | | |
lola_kn | maximin | spatial locations of 1535 weather stations | data.frame | 1535 | 2 |
Orthodont | lqmm | Growth curve data on an orthdontic measurement | nfnGroupedData | 108 | 4 |
labor | lqmm | Labor Pain Data | data.frame | 358 | 4 |
nlmixr2Keywords | nlmixr2est | A list and description of the fields in the nlmxir2 object | data.frame | 41 | 2 |
jobs | resumer | Prices of 50,000 round cut diamonds. | data.frame | 27 | 10 |
Europe | BioStatR | Durรฉes de travail en Europe | data.frame | 25 | 2 |
Extrait_Taille | BioStatR | Mesures de fruits d'arbustes | data.frame | 80 | 3 |
Mesures | BioStatR | Mesures de fruits d'arbustes | data.frame | 252 | 3 |
Mesures5 | BioStatR | Mesures de fruits d'arbustes | data.frame | 252 | 5 |
Quetelet | BioStatR | Indices de Quetelet | data.frame | 66 | 3 |
ct | bamdit | Diagnosis of appendicities with computer tomography scans | data.frame | 51 | 17 |
diabetes | bamdit | Systematic review which compares the accuracy of HbA1c vs FPG in diabetes | data.frame | 38 | 9 |
ep | bamdit | Ectopic pregnancy vs. all other pregnancies data | data.frame | 21 | 8 |
glas | bamdit | Tumor markers in the diagnosis of primary bladder cancer. | data.frame | 45 | 7 |
gould | bamdit | Accuracy of Positron Emission Tomography for Diagnosis of Pulmonary Nodules and Mass Lesions | data.frame | 31 | 6 |
mri | bamdit | Diagnosis of lymph node metastasis with magnetic resonance imaging | matrix | 10 | 4 |
rapt | bamdit | Systematic reviews of clinical decision tools for acute abdominal pain | data.frame | 13 | 13 |
safdar05 | bamdit | Diagnosis of Intravascular Device-Related Bloodstream Infection | data.frame | 78 | 8 |
scheidler | bamdit | Radiological evaluation of lymph node metastases in patients with cervical cancer: a meta-analysis. | data.frame | 46 | 7 |
skin | bamdit | Accuracy of Computer-Aided Diagnosis of Melanoma: A Meta-analysis. | data.frame | 70 | 17 |
skin2 | bamdit | Accuracy of Computer-Aided Diagnosis of Melanoma: A Comparative Meta-analysis. | data.frame | 14 | 12 |
all_neon_tick_data | mvgam | NEON Amblyomma and Ixodes tick abundance survey data | grouped_df | 3505 | 24 |
portal_data | mvgam | Portal Project rodent capture survey data | data.frame | 199 | 10 |
Fertilizer | mvinfluence | Fertilizer Data | data.frame | 8 | 3 |
aapl | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 1260 | 7 |
alphabet | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 26 | 2 |
anscombe_obs | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 44 | 3 |
athletes | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 11538 | 12 |
barley | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 120 | 4 |
bls | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 1708 | 3 |
bls_unemployment | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 7470 | 3 |
caltrain | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 78 | 7 |
civilizations | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 51 | 7 |
congress | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 887 | 3 |
crimea | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 72 | 3 |
diamonds_obs | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 53940 | 2 |
dji | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 5080 | 7 |
driving | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 55 | 4 |
gistemp | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 1644 | 2 |
income | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 49 | 4 |
iowa | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 171 | 3 |
metros | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 195 | 10 |
mobydick1 | obsplot | Sample data from Observable Plot documentation examples | character | | |
popchange | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 52 | 3 |
povcalnet | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 173 | 32 |
riaa | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 1081 | 4 |
seattle | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 1461 | 6 |
sfcases | obsplot | Sample data from Observable Plot changelog | spec_tbl_df | 1797 | 5 |
sftemp | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 732 | 3 |
simpsons | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 600 | 13 |
stateage | obsplot | Sample data from Observable Plot documentation examples | tbl_df | 468 | 3 |
stocks | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 5040 | 8 |
travelers | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 300 | 3 |
trends2020 | obsplot | Sample data from Observable Plot changelog | spec_tbl_df | 3392 | 7 |
unemployment | obsplot | Sample data from Observable Plot documentation examples | spec_tbl_df | 1708 | 3 |
data | ICSS | Sample data for Inclan/Tiao (1994) | numeric | | |
cpDNAterms | AnnotationBustR | Chloroplast DNA (cpDNA) Search Terms | data.frame | 364 | 3 |
mtDNAterms | AnnotationBustR | Mitochondrial DNA Search Terms for Animals | data.frame | 253 | 3 |
mtDNAtermsPlants | AnnotationBustR | Mitochondrial DNA Search Terms for Plants | data.frame | 248 | 3 |
rDNAterms | AnnotationBustR | Ribosomal DNA (rDNA) Search Terms | data.frame | 7 | 3 |
GBSG | mfp | German Breast Cancer Study Group | data.frame | 686 | 11 |
bodyfat | mfp | percentage of body fat determined by underwater weighing | data.frame | 252 | 17 |
Chemistry | Qtools | A-level Chemistry Scores | data.frame | 31022 | 7 |
Orthodont | Qtools | Growth curve data on an orthdontic measurement | nfnGroupedData | 108 | 4 |
esterase | Qtools | Esterase Essay Data | data.frame | 113 | 2 |
labor | Qtools | Labor Pain Data | data.frame | 358 | 4 |
sqnData0 | SQN | example data | matrix | 6000 | 2 |
B5MS | mgm | Example Datasets in the mgm Package | matrix | 500 | 5 |
Fried2015 | mgm | Example Datasets in the mgm Package | list | | |
PTSD_data | mgm | Example Datasets in the mgm Package | list | | |
autism_data | mgm | Example Datasets in the mgm Package | list | | |
autism_data_large | mgm | Example Datasets in the mgm Package | list | | |
dataGD | mgm | Example Datasets in the mgm Package | matrix | 3000 | 7 |
fruitfly_data | mgm | Example Datasets in the mgm Package | list | | |
mgm_data | mgm | Example Datasets in the mgm Package | list | | |
modnw | mgm | Example Datasets in the mgm Package | matrix | 858 | |
msq_p3 | mgm | Example Datasets in the mgm Package | data.frame | 3896 | 3 |
msq_p5 | mgm | Example Datasets in the mgm Package | data.frame | 3896 | 5 |
mvar_data | mgm | Example Datasets in the mgm Package | list | | |
restingstate_data | mgm | Example Datasets in the mgm Package | list | | |
symptom_data | mgm | Example Datasets in the mgm Package | list | | |
farmer2005 | desiR | Breast cancer microarray dataset | data.frame | 1000 | 7 |
tnrs_testfile | TNRS | 100 scientific names. | data.frame | 100 | 2 |
currencies | FinancialInstrument | currency metadata to be used by 'load.instruments' | data.frame | 26 | 1 |
future_series | FinancialInstrument | Constructors for series contracts | data.frame | 712 | 1 |
root_contracts | FinancialInstrument | future metadata to be used by 'load.instruments' | data.frame | 95 | 1 |
PGgame | anim.plots | Data from 20 rounds of a public goods game with punishment | xtabs | | |
cities | anim.plots | Cities near the Grande Armee's march on Moscow | data.frame | 20 | 3 |
gm_data | anim.plots | Gapminder GDP, life expectancy and population data | grouped_df | 18043 | 6 |
hurricanes | anim.plots | Wind speed data for hurricanes in 2009 | data.frame | 1371 | 23 |
temps | anim.plots | Temperatures for the Grande Armee's march on Moscow | data.frame | 9 | 5 |
troops | anim.plots | Troop numbers for the Grande Armee's march on Moscow | data.frame | 51 | 5 |
CIVLABOR | deseats | Monthly Civilian Labor Force Level in the USA | ts | | |
CONSUMPTION | deseats | Quarterly Real Final Consumption Expenditure for Australia | ts | 242 | 1 |
COVID | deseats | Daily Confirmed New COVID-19 Cases in Germany | ts | | |
DEATHS | deseats | Monthly Deaths in Germany | ts | | |
ENERGY | deseats | Monthly Total Production and Distribution of Electricity, Gas, Steam, and Air Conditioning for Germany | ts | 390 | 1 |
EXPENDITURES | deseats | Quarterly Personal Consumption Expenditures in the USA | ts | | |
GDP | deseats | Quarterly US GDP | ts | 292 | 1 |
HOUSES | deseats | Monthly New One Family Houses Sold in the USA | ts | 252 | 1 |
LIVEBIRTHS | deseats | Monthly Live Births in Germany | ts | | |
NOLABORFORCE | deseats | Monthly Number of US Persons Not in the Labor Force | ts | | |
RAINFALL | deseats | Monthly Average Rainfall in Germany | ts | | |
RETAIL | deseats | Monthly Total Volume of Retail Trade in Germany | ts | 348 | 1 |
SAVINGS | deseats | Quarterly Savings of Private Households in Germany | ts | | |
SUNSHINE | deseats | Monthly Hours of Sunshine in Germany | ts | | |
TEMPERATURE | deseats | Monthly Average Temperature in Germany | ts | | |
Chen2017 | sechm | Example dataset | SummarizedExperiment | | |
sampleData2 | rrtable | Sample data for pptxList A dataset containing five objects for reproducible research | data.frame | 13 | 3 |
sampleData3 | rrtable | Sample data for pptxList A dataset containing five objects for reproducible research | data.frame | 24 | 5 |
ptsd_data | inet | Datasets included in inet package | matrix | 344 | 17 |
lizards | brglm | Habitat Preferences of Lizards | data.frame | 23 | 6 |
extdata_fnames | arctools | Names of exemplary accelerometry data file. | character | | |
ozone | bfp | Ozone data from Breiman and Friedman, 1985 | data.frame | 366 | 13 |
bloodcontrol | ABPS | Blood samples from different individuals. | data.frame | 13 | 12 |
blooddoping | ABPS | Blood samples from an athlete convicted of doping. | data.frame | 13 | 11 |
iycfData | riycf | Infant and Young Children Indicators Sample Dataset | data.frame | 359 | 46 |
signals | runcharter | #' 220 grouped observations over time. | tbl_df | 220 | 3 |
growth | pampe | Example Data for pampe function from the pampe package | data.frame | 61 | 25 |
latesummer | rLakeAnalyzer | Late Summer Profile | data.frame | 881 | 6 |
ChemicalManufacturingProcess | AppliedPredictiveModeling | Chemical Manufacturing Process Data | data.frame | 176 | 58 |
abalone | AppliedPredictiveModeling | Abalone Data | data.frame | 4177 | 9 |
bio | AppliedPredictiveModeling | Hepatic Injury Data | data.frame | 281 | 184 |
cars2010 | AppliedPredictiveModeling | Fuel Economy Data | data.frame | 1107 | 14 |
cars2011 | AppliedPredictiveModeling | Fuel Economy Data | data.frame | 245 | 14 |
cars2012 | AppliedPredictiveModeling | Fuel Economy Data | data.frame | 95 | 14 |
chem | AppliedPredictiveModeling | Hepatic Injury Data | data.frame | 281 | 192 |
classes | AppliedPredictiveModeling | Two Class Example Data | factor | | |
concrete | AppliedPredictiveModeling | Compressive Strength of Concrete from Yeh (1998) | data.frame | 1030 | 9 |
diagnosis | AppliedPredictiveModeling | Alzheimer's Disease CSF Data | factor | | |
fingerprints | AppliedPredictiveModeling | Permeability Data | matrix | 165 | 1107 |
injury | AppliedPredictiveModeling | Hepatic Injury Data | factor | | |
logisticCreditPredictions | AppliedPredictiveModeling | Logistic Regression Predictions for the Credit Data | data.frame | 200 | 4 |
mixtures | AppliedPredictiveModeling | Compressive Strength of Concrete from Yeh (1998) | data.frame | 1030 | 9 |
permeability | AppliedPredictiveModeling | Permeability Data | matrix | 165 | 1 |
predictors | AppliedPredictiveModeling | Alzheimer's Disease CSF Data | data.frame | 333 | 130 |
predictors | AppliedPredictiveModeling | Alzheimer's Disease CSF Data | data.frame | 208 | 2 |
schedulingData | AppliedPredictiveModeling | HPC Job Scheduling Data | data.frame | 4331 | 8 |
segmentationOriginal | AppliedPredictiveModeling | Cell Body Segmentation | data.frame | 2019 | 119 |
solTestX | AppliedPredictiveModeling | Solubility Data | data.frame | 316 | 228 |
solTestXtrans | AppliedPredictiveModeling | Solubility Data | data.frame | 316 | 228 |
solTestY | AppliedPredictiveModeling | Solubility Data | numeric | | |
solTrainX | AppliedPredictiveModeling | Solubility Data | data.frame | 951 | 228 |
solTrainXtrans | AppliedPredictiveModeling | Solubility Data | data.frame | 951 | 228 |
solTrainY | AppliedPredictiveModeling | Solubility Data | numeric | | |
keyboards | wordler | Keyboard layouts for printing a wordler game at the console. | list | | |
qdap_dict | wordler | All five-letter words from the Nettalk Corpus Syllable Data Set. | character | | |
ubuntu_dict | wordler | All five-letter words from the Ubuntu dictionary. | character | | |
wordle_allowed | wordler | All words used to validate guesses by the original WORDLE game. | character | | |
wordle_answers | wordler | All words used as potential answers by the original WORDLE game. | character | | |
ca_tiles | rmapzen | Vector tiles the contain California | mapzen_vector_tiles | | |
marina_walks | rmapzen | Pedestrian isochrones from the Berkeley Marina for 10 and 15 minutes | mapzen_isochrone_list | | |
marina_walks_polygons | rmapzen | Pedestrian isochrones from the Berkeley Marina for 10 and 15 minutes, as polygons | mapzen_isochrone_list | | |
oakland_public | rmapzen | 25 search results for "Oakland Public library branch" | mapzen_geo_list | | |
PROseq | BRGenomics | PRO-seq data from Drosophila S2 cells | GRanges | | |
PROseq_paired | BRGenomics | PRO-seq data from Drosophila S2 cells | GRanges | | |
txs_dm6_chr4 | BRGenomics | Ensembl transcripts for Drosophila melanogaster, dm6, chromosome 4. | GRanges | | |
adult | fairmodels | Adult dataset | data.frame | 32561 | 15 |
adult_test | fairmodels | Adult test dataset | data.frame | 16281 | 15 |
compas | fairmodels | Modified COMPAS dataset | data.frame | 6172 | 7 |
german | fairmodels | Modified German Credit data dataset | data.frame | 1000 | 10 |
books | litRiddle | Measurements of 401 novels | data.frame | 401 | 25 |
frequencies | litRiddle | Word frequencies (5000 most frequent words) of 401 novels. | matrix | 401 | 5000 |
motivations | litRiddle | Reviewers' motivations for their scores (if given) | data.frame | 211031 | 8 |
respondents | litRiddle | Respondents' Answers | data.frame | 13541 | 29 |
reviews | litRiddle | Reviewers' scores | data.frame | 448055 | 7 |
dataset.all.species | sperich | Angiosperm Dataset | data.frame | 45677 | 3 |
dataset.height | sperich | Height-Information Dataset | data.frame | 7626 | 3 |
dataset.landwater | sperich | Land-Water-Information Dataset | data.frame | 8455 | 3 |
Admission | coreSim | Graduate school admissions data | data.frame | 400 | 4 |
bolsafam | randomMachines | Bolsa Famรญlia Dataset | data.frame | 5564 | 11 |
ionosphere | randomMachines | Ionosphere Dataset | spec_tbl_df | 351 | 35 |
whosale | randomMachines | Wholesale Dataset | spec_tbl_df | 440 | 8 |
akcoast | pathroutr | Alaska coastline | sf | 273 | 6 |
land_barrier | pathroutr | land barrier | sf | 19 | 1 |
poi | pathroutr | points of interest | sf | 67 | 1 |
Carcinoma | ggpcp | Data set: Assessment of Carcinoma slides | tbl_df | 118 | 9 |
nasa | ggpcp | Data set: NASA - Data Expo 2006 | data.frame | 41472 | 15 |
ant.final | GoodFibes | Ant muscle fibers finalized | list | | |
ant.raw | GoodFibes | Raw ant muscle fibers | list | | |
fortmax | eva | | data.frame | 100 | 11 |
lowestoft | eva | | matrix | 51 | 10 |
carscomplete | plsdepot | carscomplete data set | data.frame | 24 | 6 |
carsmissing | plsdepot | carsmissing data set | data.frame | 24 | 6 |
cornell | plsdepot | Cornell data set | data.frame | 12 | 8 |
linnerud | plsdepot | Linnerud data set | data.frame | 20 | 6 |
ropes | plsdepot | Climbing Ropes data set | data.frame | 101 | 7 |
vehicles | plsdepot | Vehicles data set | data.frame | 30 | 16 |
actuary_salaries | ExamPAData | DW Simpson actuarial salary data | spec_tbl_df | 138 | 6 |
apartment_apps | ExamPAData | Apartment Apps | data.frame | 1430 | 41 |
auto_claim | ExamPAData | Automotive claims | spec_tbl_df | 10296 | 29 |
bank_loans | ExamPAData | Bank Loans | spec_tbl_df | 41188 | 21 |
bike_sharing_demand | ExamPAData | Bike sharing demand | data.frame | 17376 | 10 |
boston | ExamPAData | Boston | spec_tbl_df | 506 | 14 |
customer_phone_calls | ExamPAData | Customer Phone Calls | spec_tbl_df | 10000 | 14 |
customer_value | ExamPAData | Customer Value | spec_tbl_df | 48842 | 8 |
exam_pa_titanic | ExamPAData | Exam PA Titanic | spec_tbl_df | 906 | 11 |
health_insurance | ExamPAData | Health insurance | spec_tbl_df | 1338 | 7 |
june_pa | ExamPAData | June_pa | spec_tbl_df | 23137 | 14 |
patient_length_of_stay | ExamPAData | Patient Length of Stay | spec_tbl_df | 10000 | 13 |
patient_num_labs | ExamPAData | Patient Number of Labs | spec_tbl_df | 10000 | 14 |
pedestrian_activity | ExamPAData | Pedestrian activity | data.frame | 11373 | 7 |
readmission | ExamPAData | Readmission | spec_tbl_df | 66782 | 9 |
student_success | ExamPAData | Student Success | spec_tbl_df | 585 | 33 |
travel_insurance | ExamPAData | Travel insurance data | data.frame | 10000 | 7 |
travel_spending | ExamPAData | Travel spending data | data.frame | 4884 | 11 |
cmrdata_sim | cmR | Simulated data for CMR package. | array | | |
input_sim | cmR | Simulated data for CMR package. | numeric | | |
maxresp_sim | cmR | Simulated data for CMR package. | array | | |
WQ_Q | hydroEvents | Example water quality and streamflow data | list | | |
dataBassRiver | hydroEvents | Streamflow data | numeric | | |
dataCatchment | hydroEvents | Catchment data | list | | |
dataLoch | hydroEvents | Rainfall data | numeric | | |
data_P_WL | hydroEvents | Example sub-daily rainfall and tidal water level data | list | | |
liver | goweragreement | Ordinal data from a radiological study of congenital diaphragmatic hernia. | data.frame | 47 | 4 |
SMSA | OkNNE | Standard Metropolitan Statistical Areas | data.frame | 59 | 15 |
Maize_wqs | Ghat | The Wisconsin Quality Synthetic (WQS) maize population datasets. | list | | |
pbc | tauProcess | Mayo Clinic Primary Biliary Cholangitis Data | data.frame | 258 | 3 |
prostate | depthTools | Gene Expression Data from Tumoral and Normal Prostate Samples and Labels | matrix | 50 | 101 |
data_paper | CPNCoverageAnalysis | Example of the dataset used in the paper. | data.frame | 4697 | 3 |
data_test | CPNCoverageAnalysis | Test example dataset. | data.frame | 65 | 3 |
bipartite | cbl | Simulated data | list | | |
cellphones | AHPGaussian | Decision Matrix | data.frame | 5 | 5 |
warships | AHPGaussian | Decision Matrix | data.frame | 9 | 5 |
fitted_prclmm | pencal | A fitted PRC LMM | list | | |
fitted_prcmlpmm | pencal | A fitted PRC MLPMM | list | | |
pbc2data | pencal | pbc2 dataset | list | | |
finalized_stroopdata | prepdat | Finalized Table 'prepdat::prep()' returns for 'stroopdata' According to the Example in 'prepdat::prep()'. | data.frame | 15 | 98 |
stroopdata | prepdat | Reaction-times and accuracy for color naming in a Stroop task (e.g., Stroop, 1935). | data.frame | 5400 | 10 |
example_iadf | iadf | example_iadf | data.frame | 135 | 30 |
example_rwl | iadf | example_rwl | data.frame | 135 | 30 |
karate | hydra | Zachary's karate club network data | list | | |
stroke | multiCA | Stroke types over time | data.frame | 45 | 3 |
WFO.example | WorldFlora | World Flora Online (WFO) taxonomic backbone example data set | data.frame | 13 | 19 |
vascular.families | WorldFlora | Orders and Higher Level Classifications of Vascular Plants | data.frame | 476 | 10 |
titanic | vip | Survival of Titanic passengers | data.frame | 1309 | 6 |
titanic_mice | vip | Survival of Titanic passengers | mild | | |
nhefs_weights | tidysmd | NHEFS with various propensity score weights | tbl_df | 1566 | 14 |
HIV | qrNLMM | HIV viral load study | data.frame | 361 | 6 |
Soybean | qrNLMM | Growth of soybean plants | data.frame | 412 | 5 |
quijote_words | clustringr | Distinct words in Cervantes' "Don Quijote". | tbl_df | 22842 | 3 |
ros1_ts | tsSelect | "Time Series sample" | ts | | |
ros2_ts | tsSelect | "Time Series sample 2" | ts | | |
ais | lqr | Australian institute of sport data | data.frame | 202 | 14 |
resistance | lqr | Tumor-cell resistance to death | data.frame | 425 | 3 |
AMSP | UKFE | National River Flow Archive (NRFA) annual maximum data for sites suitable for pooling | data.frame | 26539 | 3 |
NRFAData | UKFE | National River Flow Archive descriptors and calculated statistics for sites suitable for pooling | data.frame | 543 | 27 |
QMEDData | UKFE | National River Flow Archive descriptors and calculated statistics for sites suitable for QMED & pooling | data.frame | 897 | 26 |
ThamesPQ | UKFE | Kingston upon Thames daily flow and catchment precipitation 2000-10-01 to 2015-09-30 | data.frame | 5478 | 3 |
UKOutline | UKFE | UK outline | data.frame | 3867 | 2 |
Simdata | TGST | Simulated data for package illustration | data.frame | 8000 | 2 |
ennet_dailies | ennet | Daily extracts of topics dataset from en-net online forum | tbl_df | 30370 | 9 |
ennet_hourlies | ennet | Hourly extracts of topics dataset from en-net online forum | tbl_df | 643844 | 8 |
ennet_themes | ennet | Themes from en-net forum retrieved on 17 January 2021 | tbl_df | 17 | 2 |
ennet_topics | ennet | Topics from en-net forum retrieved on 17 January 2021 | tbl_df | 3288 | 7 |
ICU_data | stratamatch | Demographics and comorbidities of 10,157 ICU patients | tbl_df | 10157 | 13 |
dataAr1 | saeHB.panel | Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model | data.frame | 100 | 6 |
dataAr1Ns | saeHB.panel | Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model with Non Sampled Area | data.frame | 100 | 6 |
dataPanel | saeHB.panel | Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model when 'rho = 0' | data.frame | 100 | 6 |
dataPanelNs | saeHB.panel | Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model when 'rho = 0' with Non Sampled Area | data.frame | 100 | 6 |
beetles | cooccur | Beetle occurrence data from (Ulrich and Zalewski 2006). | data.frame | 71 | 17 |
finches | cooccur | Finch occurrence data from (Sanderson 2000). | data.frame | 13 | 17 |
rodents | cooccur | Rodent occurrence data from (Brown and Kurzius 1987). | data.frame | 16 | 39 |
india | gamboostLSS | Malnutrition of Children in India (DHS, 1998-99) | data.frame | 4000 | 7 |
india.bnd | gamboostLSS | Malnutrition of Children in India (DHS, 1998-99) | bnd | | |
natlongsurv | kutils | Smoking, Happiness, and other survey responses | data.frame | 2867 | 29 |
example1 | Rwclust | Example Graph 1 | data.frame | 35 | 3 |
example2 | Rwclust | Example Graph 2 | data.frame | 15 | 3 |
ColesData | FAmle | Annual Maximum Sea Levels at Port Pirie, South Australia | data.frame | 65 | 2 |
floodsNB | FAmle | New Brunswick (Canada) Flood Dataset | list | | |
station01AJ010 | FAmle | Annual Maximum Daily Mean Flow Data (NB, Canada) | numeric | | |
yarns | FAmle | Yarns Failure Data | data.frame | 100 | 1 |
B.dk | Epi | Births in Denmark by year and month of birth and sex | data.frame | 1416 | 4 |
BrCa | Epi | Clinical status, relapse, metastasis and death in 2982 women with breast cancer. | data.frame | 2982 | 17 |
DMconv | Epi | Conversion to diabetes | data.frame | 1519 | 6 |
DMepi | Epi | Epidemiological rates for diabetes in Denmark 1996-2015 | data.frame | 4200 | 8 |
DMlate | Epi | The Danish National Diabetes Register. | data.frame | 10000 | 7 |
DMrand | Epi | The Danish National Diabetes Register. | data.frame | 10000 | 7 |
M.dk | Epi | Mortality in Denmark 1974 ff. | data.frame | 7800 | 6 |
N.dk | Epi | Population size in Denmark | data.frame | 8600 | 4 |
S.typh | Epi | Salmonella Typhimurium outbreak 1996 in Denmark. | data.frame | 136 | 15 |
Y.dk | Epi | Population risk time in Denmark | data.frame | 16800 | 6 |
bdendo | Epi | A case-control study of endometrial cancer | data.frame | 315 | 13 |
bdendo11 | Epi | A case-control study of endometrial cancer | data.frame | 126 | 13 |
births | Epi | Births in a London Hospital | data.frame | 500 | 8 |
blcaIT | Epi | Bladder cancer mortality in Italian males | data.frame | 55 | 4 |
brv | Epi | Bereavement in an elderly cohort | data.frame | 399 | 11 |
diet | Epi | Diet and heart data | data.frame | 337 | 15 |
ewrates | Epi | Rates of lung and nasal cancer mortality, and total mortality. | data.frame | 150 | 5 |
gmortDK | Epi | Population mortality rates for Denmark in 5-years age groups. | data.frame | 418 | 21 |
hivDK | Epi | hivDK: seroconversion in a cohort of Danish men | data.frame | 297 | 7 |
lep | Epi | An unmatched case-control study of leprosy incidence | data.frame | 1370 | 7 |
lungDK | Epi | Male lung cancer incidence in Denmark | data.frame | 220 | 9 |
mortDK | Epi | Population mortality rates for Denmark in 1-year age-classes. | data.frame | 1820 | 21 |
nickel | Epi | A Cohort of Nickel Smelters in South Wales | data.frame | 679 | 7 |
occup | Epi | A small occupational cohort | data.frame | 13 | 4 |
pr | Epi | Diabetes prevance as of 2010-01-01 in Denmark | data.frame | 200 | 4 |
st2alb | Epi | Clinical trial: Steno2 baseline and follow-up. | data.frame | 563 | 3 |
st2clin | Epi | Clinical trial: Steno2 baseline and follow-up. | data.frame | 750 | 5 |
steno2 | Epi | Clinical trial: Steno2 baseline and follow-up. | data.frame | 160 | 14 |
testisDK | Epi | Testis cancer incidence in Denmark, 1943-1996 | data.frame | 4860 | 4 |
thoro | Epi | Thorotrast Study | data.frame | 2470 | 14 |
dataEB | saebnocov | Sample Data for Practice | data.frame | 1563 | 3 |
api_info_reference | tidygeocoder | Geocoding service links and information | tbl_df | 13 | 5 |
api_key_reference | tidygeocoder | API key environmental variables | tbl_df | 10 | 2 |
api_parameter_reference | tidygeocoder | Geocoding service API parameter reference | tbl_df | 72 | 5 |
batch_limit_reference | tidygeocoder | Geocoding batch size limits | tbl_df | 6 | 2 |
louisville | tidygeocoder | Louisville, Kentucky street addresses | spec_tbl_df | 50 | 6 |
min_time_reference | tidygeocoder | Minimum time required per query | tbl_df | 9 | 3 |
sample_addresses | tidygeocoder | Sample addresses for testing | tbl_df | 9 | 2 |
my_appsflyer_data | appsflyeR | Sample of digital marketing data from AppsFlyer downloaded by means of the Windsor.ai API. | data.frame | 14 | 5 |
exReadDataObj | ProliferativeIndex | TCGA ACC data set output from readDataForPI function | list | | |
exVSTPI | ProliferativeIndex | TCGA ACC data set output from calculatePI function | numeric | | |
vstTCGA_ACCData_sub | ProliferativeIndex | TCGA ACC data set | data.frame | 20501 | 10 |
binarizationExample | BiTrinA | An artificial data set consisting of ten artificial feature vectors. | matrix | 10 | |
trinarizationExample | BiTrinA | An artificial data set consisting of ten artificial feature vectors. | matrix | 100 | |
landed | funneljoin | Example dataset of landing events | tbl_df | 11 | 2 |
registered | funneljoin | Example dataset of registration events | tbl_df | 10 | 2 |
Cholesterol | qrLMM | Framingham cholesterol study | data.frame | 1044 | 6 |
Orthodont | qrLMM | Growth curve data on an orthdontic measurement | data.frame | 108 | 4 |
alfred_vintages | midasml | ALFRED monthly and quarterly series vintages | list | | |
market_ret | midasml | SNP500 returns | data.frame | 3397 | 2 |
rgdp_dates | midasml | Real GDP release dates | tbl_df | 84 | 6 |
rgdp_vintages | midasml | Real GDP vintages | data.frame | 31208 | 3 |
us_rgdp | midasml | US real GDP data with several high-frequency predictors | list | | |
AetLTR | TE | LTR retrotransposons in _Aegilops tauschii_ | tbl_df | 18024 | 14 |
AlyLTR | TE | LTR retrotransposons in _Arabidopsis lyrata_ | tbl_df | 397 | 7 |
a3_hil | SafeVote | Tideman a3_hil | matrix | 989 | 15 |
a4_hil | SafeVote | Tideman a4_hil | matrix | 43 | 14 |
a53_hil | SafeVote | Tideman a53_hil | matrix | 460 | 10 |
dublin_west | SafeVote | Dublin West | data.frame | 29988 | 9 |
food_election | SafeVote | Food Election | data.frame | 20 | 5 |
ims_approval | SafeVote | IMS Approval | data.frame | 620 | 10 |
ims_election | SafeVote | IMS Election | data.frame | 620 | 10 |
ims_plurality | SafeVote | IMS Plurality | data.frame | 620 | 10 |
ims_score | SafeVote | IMS Score | data.frame | 620 | 10 |
ims_stv | SafeVote | IMS STV | data.frame | 620 | 10 |
uk_labour_2010 | SafeVote | UK Labour Party Leader 2010 | data.frame | 266 | 5 |
yale_ballots | SafeVote | Yale Faculty Senate 2016 | data.frame | 479 | 44 |
dd | MiSPU | The estimate of Dirichlet-multinomial distribution | list | | |
throat.meta | MiSPU | Meta data of the throat microbiome samples. | data.frame | 60 | 16 |
throat.otu.tab | MiSPU | OTU count table from 16S sequencing of the throat microbiome samples. | data.frame | 60 | 856 |
throat.tree | MiSPU | UPGMA tree of the OTUs from 16S sequencing of the throat microbiome samples. | phylo | | |
ExPanD_config_russell_3000 | ExPanDaR | Default Configuration to use with ExPanD and the Russell 3000 Data Set | list | | |
ExPanD_config_worldbank | ExPanDaR | Default Configuration to Use with ExPanD and the 'worldbank' Data Set | list | | |
russell_3000 | ExPanDaR | Annual Financial Accounting and Stock Return Data for a Sample of Russell 3000 Firms (2013-2016) | data.frame | 8777 | 24 |
russell_3000_data_def | ExPanDaR | Data Definitions for 'russell_3000' Data Set | data.frame | 24 | 3 |
worldbank | ExPanDaR | A Snapshot of Macroeconomic Data as Provided by the World Bank API (1960 - 2018) | data.frame | 9248 | 26 |
worldbank_data_def | ExPanDaR | Data Definitions for 'worldbank' Data Set | data.frame | 26 | 3 |
worldbank_var_def | ExPanDaR | Variable Definitions to Construct an Analysis Sample Based on the 'worldbank' Data Set | data.frame | 23 | 4 |
azteca | Rsampling | An experiment on ant recruitment | data.frame | 21 | 3 |
embauba | Rsampling | Vine infestation on Cecropia trees | data.frame | 152 | 2 |
peucetia | Rsampling | Preference of hunting spiders by hairy leaves | data.frame | 27 | 6 |
pielou | Rsampling | Aphids recorded on goldenrods | data.frame | 10 | 12 |
rhyzophora | Rsampling | Allometry in mangrove trees | data.frame | 24 | 4 |
drugdemo | immcp | Datasets Demo dataset | list | | |
toydata | CHMM | Toy example - observations for 5 correlated samples. | matrix | 1000 | 5 |
toystatus | CHMM | Toy example - status for 5 correlated samples. | matrix | 1000 | 5 |
data100x15 | RankAggSIgFUR | Simulated 100 X 15 Data | tbl_df | 100 | 16 |
data240x4 | RankAggSIgFUR | PrefLib 240 X 4 Data | tbl_df | 240 | 5 |
data400x15 | RankAggSIgFUR | Simulated 400 X 15 Data | data.frame | 400 | 16 |
data50x15 | RankAggSIgFUR | Simulated 50 X 15 Data | tbl_df | 50 | 16 |
nh0506 | natstrat | Homocysteine and smoking example data | data.frame | 2928 | 11 |
nh0506_3groups | natstrat | Homocysteine and smoking example data with multiple control groups | data.frame | 4457 | 11 |
stlouis | mix | St. Louis Risk Research Project | matrix | 69 | 7 |
anoctua | blmeco | Presence-absence data of Little owls in nest boxes | data.frame | 361 | 3 |
blackstork | blmeco | Breeding success of Black storks in Latvia | data.frame | 1130 | 3 |
cortbowl | blmeco | stress hormone data of nestling barn owls which were either treated with a corticosterone-implant or with a placebo-implant as control | data.frame | 287 | 6 |
ellenberg | blmeco | Hohenheim groundwater table experiment of Heinz Ellenberg | data.frame | 264 | 29 |
frogs | blmeco | Counts of the number of frogs in a water body | data.frame | 481 | 10 |
mdat | blmeco | Simulated set of correlated variables | data.frame | 100 | 6 |
nightingales | blmeco | Nightingale territory occupancy data | array | | |
parusmajor | blmeco | Number of migrating Great tits | data.frame | 434 | 3 |
periparusater | blmeco | The data contain morphological measurements taken from museum skins of Coal tits (Periparus ater) | data.frame | 19 | 6 |
pondfrog | blmeco | Fake Data of the Numbers of Frogs in Ponds | data.frame | 130 | 9 |
pondfrog1 | blmeco | Fake Data: Number of Frogs in Ponds | data.frame | 130 | 4 |
redstart | blmeco | Common Redstart (Phoenicurus phoenicurus) counts | data.frame | 342 | 5 |
resprouts | blmeco | Survival data of tree sprouts | data.frame | 41 | 4 |
roostingsiteuse | blmeco | Roosting site use by little owls | data.frame | 42 | 5 |
spermdepletion | blmeco | Sperm depletion data in a hermaphrodite sea slug | data.frame | 264 | 6 |
survival_swallows | blmeco | Telemetry data of Barn swallow fledglings | list | | |
swallowfarms | blmeco | Number of fledged Barn Swallows per nest | data.frame | 63 | 6 |
swallows | blmeco | Data set with number of nesting swallows per barn | data.frame | 27 | 6 |
wildflowerfields | blmeco | Territory numbers of Whitethroat in wildflowerfields | data.frame | 136 | 8 |
wingbowl | blmeco | Growth rate data of Barn owl nestlings and corticosterone | data.frame | 209 | 7 |
yellow_bellied_toad | blmeco | Site-occupancy data for Yellow-bellied toads | list | | |
nonlineardata | controlfunctionIV | nonlineardata | data.frame | 3733 | 9 |
weight_behavior | hdbma | Weight_Behavior Data Set | data.frame | 691 | 15 |
SCUD | npsm | Cyclone Data | data.frame | 21 | 3 |
acov231 | npsm | Analysis of Covariance Example for a two by three two-way design | data.frame | 33 | 4 |
baseball_players1000 | npsm | Career Information for a Random Sample of 1000 Baseball Players | data.frame | 1000 | 28 |
bb2010 | npsm | Batting statistics for the 2010 baseball season. | data.frame | 122 | 3 |
blood.plasma | npsm | Blood plasma measurements related to total triglyceride level | matrix | 13 | 8 |
brewers1982 | npsm | Basic Summaries of Boxscores for the Milwaukee Brewers 1982 Season | data.frame | 163 | 8 |
cancertrt | npsm | Survival time based on two treatments | data.frame | 17 | 3 |
cloud | npsm | Cloud Dewpoint | data.frame | 19 | 2 |
energy | npsm | Energy as a Function of temperature difference. | data.frame | 24 | 2 |
firstbase | npsm | Rounding First Base. | data.frame | 22 | 3 |
hemorrhage | npsm | Hemorrhage data from Dupont. | data.frame | 71 | 3 |
hodgkins | npsm | Relapse-Free Survival Times for Hodgkin's Disease Patients | data.frame | 49 | 3 |
huitema496 | npsm | Analysis of Covarince Data Set | matrix | 16 | 4 |
insulation | npsm | Insulating Fluid Data | data.frame | 76 | 2 |
latour | npsm | Chateau Latour Wine Data | data.frame | 44 | 4 |
plank | npsm | Plank data | data.frame | 64 | 4 |
poly | npsm | A Simulated Polynomial Data Set. | matrix | 100 | 2 |
prostate | npsm | DES for treatment of prostate cancer. | data.frame | 38 | 8 |
qhic | npsm | qhic | data.frame | 40 | 2 |
quail2 | npsm | Quail from a two-factor experiment. | data.frame | 30 | 2 |
rs | npsm | Simulated Regression Model | data.frame | 50 | 2 |
seinfeld | npsm | Seinfeld - the sitcom - viewership counts by episode | data.frame | 180 | 4 |
sievers | npsm | Doksum and Sievers rat data | data.frame | 45 | 2 |
sim_class2 | npsm | A simulated classification example with two variables and two classes (labels). | data.frame | 1000 | 4 |
simon | npsm | Simon (the memory game) dataset | data.frame | 31 | 3 |
sincos | npsm | Sine Cosine Model | data.frame | 197 | 2 |
speed | npsm | Predict top speed based on miles per gallon | data.frame | 82 | 2 |
turtle | npsm | Turtle Data | data.frame | 48 | 4 |
weather | npsm | January Weather Data for Kalamazoo | matrix | 96 | 13 |
ribo.prof | babel | Sample ribosome profiling data | list | | |
grid | CVN | Data for a grid of graphs (3 x 3) | list | | |
realdata_alpha | SPPcomb | A list of matrices containing value of alpha at each location. | list | | |
realdata_covariates | SPPcomb | A data list of matrices containing covariates of cases and controls. | list | | |
belgium_parliament | tokenizers.bpe | Dataset from 2017 with Questions asked in the Belgium Federal Parliament | data.frame | 2000 | 3 |
simulation1 | hosm | Simulation 1 for High Order Spatial Matrix | data.frame | 4 | 5 |
simulation2 | hosm | Simulation 2 for High Order Spatial Matrix | data.frame | 5 | 6 |
simulation3 | hosm | Simulation 3 for High Order Spatial Matrix | data.frame | 5 | 6 |
simulation4 | hosm | Simulation 4 for High Order Spatial Matrix | data.frame | 4 | 5 |
simulation5 | hosm | Simulation 5 for High Order Spatial Matrix | data.frame | 4 | 5 |
Body | OTE | Exploring Relationships in Body Dimensions | data.frame | 507 | 25 |
Galaxy | OTE | Radial Velocity of Galaxy NGC7531 | data.frame | 323 | 5 |
ict_pop | gustave | Sampling frame of the Information and communication technologies (ICT) survey | data.frame | 7670 | 5 |
ict_sample | gustave | Sample of the Information and communication technologies (ICT) survey | data.frame | 650 | 27 |
ict_survey | gustave | Survey data of the Information and communication technologies (ICT) survey | data.frame | 506 | 11 |
lfs_samp_area | gustave | Sample of areas in the Labour force survey | data.frame | 4 | 3 |
lfs_samp_dwel | gustave | Sample of dwellings in the Labour force survey | data.frame | 80 | 6 |
lfs_samp_ind | gustave | Sample of individuals in the Labour force survey | data.frame | 116 | 5 |
fakeData | ClinicalUtilityRecal | Dataset for Recalibration Purposes | data.frame | 1000 | 2 |
sentence_example | RcppJagger | An example sentence | data.frame | 1 | 1 |
accident | hmmm | factory accident data | data.frame | 72 | 5 |
depression | hmmm | longitudinal study of mental depression | data.frame | 32 | 6 |
drinks | hmmm | soft-drinks data | data.frame | 269 | 5 |
kentucky | hmmm | Kentucky traffic accident data | data.frame | 50 | 4 |
madsen | hmmm | Madsen data | data.frame | 72 | 5 |
polbirth | hmmm | political orientation and teenage birth control data | data.frame | 28 | 3 |
relpol | hmmm | religion and political orientation data | data.frame | 21 | 3 |
relpolbirth | hmmm | religion, political orientation and teenage birth control data | data.frame | 84 | 4 |
template_WES_data | WES | Template environmental sampling data | data.frame | 5200 | 6 |
template_WES_standard_curve | WES | Template standard curve data | data.frame | 20 | 3 |
depress | lboxcox | Depression dataset | data.frame | 8893 | 5 |
Burn | mixexp | Data from Table 4 in Gallant,Prickett, Cesarec, and Bruck(2008) | data.frame | 15 | 5 |
SneeMq | mixexp | Data from Snee and Marquart's Screening Experiment with contsrained mixture components | data.frame | 20 | 9 |
conmx | mixexp | Example constraint matrix from Piepel 1988 | matrix | 8 | |
etch | mixexp | Data from Etch rate experiment in Table 12.4 of Myers and Montgomery(2002) | data.frame | 14 | 4 |
fishp | mixexp | Data from Cornell's famous fish patty mixture process variable experiment | data.frame | 56 | 7 |
diabetes | nestfs | Diabetes data with interaction terms | data.frame | 442 | 65 |
DEU_PISA2012 | pairwise | Data from PISA 2012 - German Sample | list | | |
KCT | pairwise | Knox Cube Test Data from Wright & Stone (1979) | data.frame | 35 | 18 |
Neoffi5 | pairwise | Polytomous example data in Rost 2004 | matrix | 1000 | |
bfiN | pairwise | 5 polytomous personality items | data.frame | 2800 | 5 |
bfiN_miss | pairwise | 5 polytomous personality items | data.frame | 2800 | 5 |
bfi_cov | pairwise | Covariates to the bfiN Data | data.frame | 2800 | 3 |
cog | pairwise | Math PISA (2003) data | data.frame | 4660 | 34 |
cogBOOKLET | pairwise | Booklet allocation table for Math PISA (2003) data | data.frame | 31 | 5 |
kft5 | pairwise | Dichotomous example data in Rost 2004 | matrix | 300 | 5 |
sim200x3 | pairwise | Simulated Data | data.frame | 200 | 3 |
SBM_net | CommKern | Simulated functional and structural connectivity with nested hierarchical community structure | spinglass_net | | |
simasd_array | CommKern | Simulated Array | array | | |
simasd_comm_df | CommKern | Simulated partitions of nodes to communities from HMS algorithm | data.frame | 80 | 49 |
simasd_covars | CommKern | Simulated demographics dataset modeled of a subset of the preprocessed ABIDE database | data.frame | 49 | 8 |
simasd_hamil_df | CommKern | Simulated Hamiltonian values from HMS algorithm | data.frame | 49 | 2 |
BCI | biosampleR | Barro-Colorado Island Tree Counts | data.frame | 50 | 225 |
example_cli | imsig | Example clinical data file for survival analysis with ImSig | data.frame | 59 | 2 |
example_data | imsig | Example transcriptomics data | data.frame | 568 | 60 |
sig | imsig | ImSig genes | data.frame | 569 | 2 |
exData | rKOMICS | Example dataset | list | | |
matrices | rKOMICS | Example cluster matrices | list | | |
build_ref | GwasDataImport | | data.frame | 236061 | 4 |
mart36 | GwasDataImport | | Mart | | |
mart37 | GwasDataImport | | Mart | | |
mart38 | GwasDataImport | | Mart | | |
LR04_MISboundaries | gsloid | Marine isotope stages (MIS) boundaries. | data.frame | 232 | 7 |
lisiecki2005 | gsloid | LR04 Global Pliocene-Pleistocene Benthic d18O Stack (5.3-Myr). | data.frame | 2115 | 3 |
spratt2016 | gsloid | Global Sea Level Reconstruction using Stacked Records from 0-800 ka. | data.frame | 799 | 9 |
cyrpa_ripr | loewesadditivity | CyRPA and RIPR | data.frame | 38 | 15 |
rh5_ama1ron2 | loewesadditivity | RH5 and AMA1RON2 | data.frame | 38 | 15 |
rh5_rh4 | loewesadditivity | RH5 and RH4 | data.frame | 48 | 3 |
aids | brglm2 | The effects of AZT in slowing the development of AIDS symptoms | data.frame | 4 | 4 |
alligators | brglm2 | Alligator food choice data | data.frame | 80 | 5 |
coalition | brglm2 | Coalition data | data.frame | 314 | 7 |
endometrial | brglm2 | Histology grade and risk factors for 79 cases of endometrial cancer | data.frame | 79 | 4 |
enzymes | brglm2 | Liver Enzyme Data | data.frame | 218 | 6 |
hepatitis | brglm2 | Post-transfusion hepatitis: impact of non-A, non-B hepatitis surrogate tests | data.frame | 28 | 6 |
lizards | brglm2 | Habitat preferences of lizards | data.frame | 23 | 6 |
stemcell | brglm2 | Opinion on Stem Cell Research and Religious Fundamentalism | data.frame | 24 | 4 |
mpdta | did | County Teen Employment Dataset | data.frame | 2500 | 6 |
Sonar | MLeval | Sonar data | data.frame | 208 | 61 |
fit | MLeval | Random forest fitted object from Caret on Sonar data | train | | |
fit1 | MLeval | Random forest fitted object from Caret on Sonar data | train | | |
fit2 | MLeval | Gradient boosted machines fitted object from Caret on Sonar data | train | | |
fit3 | MLeval | Random forest fitted object from Caret on Sonar data with log-likelihood objective function | train | | |
im_fit | MLeval | Random forest fitted object from Caret on simulated imbalanced data | train | | |
preds | MLeval | Predictions from gbm on the Sonar test data | data.frame | 51 | 4 |
predsc | MLeval | Predictions from gbm and random forest on the Sonar test data | data.frame | 102 | 4 |
euro_dates | dispeRse | Coordinates and earliest dates (med cal BP) for European Neolithic sites. Dataset adapted from the supplementary information in Pinhasi et al. 2005 (https://doi.org/10.1371/journal.pbio.0030410). | SpatialPointsDataFrame | | |
euro_npp | dispeRse | Transformed Net Primary Production (NPP) from 11 ka to 4 ka at 1000 yr steps. Calculated with the Miami formula using paleoclimatic data from Beyer et al. 2020. (https://doi.org/10.1038/s41597-020-0552-1). Clipped to max=1350, squared and scaled to [0,1]. | RasterStack | | |
euro_terr | dispeRse | Reclassified terrain layer with elevation > 1750 m as barriers and rivers and coastline as corridors. Terrain reclassified from SRTM. Rivers rasterized from GSHHG (https://www.soest.hawaii.edu/pwessel/gshhg/) and coastline rasterized from rnaturalearth. | RasterLayer | | |
ppnb | dispeRse | Coordinates and earliest dates (med cal BP) for Late Pre-Pottery Neolithic B sites in the Near East. Dataset adapted from the supplementary information in Pinhasi et al. 2005 (https://doi.org/10.1371/journal.pbio.0030410). | data.frame | 9 | 3 |
BarcelonaCensusTracts | AQuadtree | Census tract borders of Barcelona city in Catalonia. | SpatialPolygonsDataFrame | | |
BarcelonaPop | AQuadtree | Radomly created population points for Barcelona city in Catalonia. | SpatialPointsDataFrame | | |
CharlestonCensusTracts | AQuadtree | Census tract borders of Charleston, SC MSA, USA. | SpatialPolygons | | |
CharlestonPop | AQuadtree | Radomly created population points for Charleston, SC MSA, USA. | SpatialPointsDataFrame | | |
GBSG2 | TH.data | German Breast Cancer Study Group 2 | data.frame | 686 | 10 |
GlaucomaM | TH.data | Glaucoma Database | data.frame | 196 | 63 |
Westbc | TH.data | Breast Cancer Gene Expression | list | | |
birds | TH.data | Habitat Suitability for Breeding Bird Communities | data.frame | 258 | 10 |
bodyfat | TH.data | Prediction of Body Fat by Skinfold Thickness, Circumferences, and Bone Breadths | data.frame | 71 | 10 |
geyser | TH.data | Old Faithful Geyser Data | data.frame | 299 | 2 |
mammoexp | TH.data | Mammography Experience Study | data.frame | 412 | 6 |
mn6.9 | TH.data | I.Q. and attitude towards science | data.frame | 2982 | 5 |
sphase | TH.data | S-phase Fraction of Tumor Cells | data.frame | 109 | 3 |
wpbc | TH.data | Wisconsin Prognostic Breast Cancer Data | data.frame | 198 | 34 |
COVID19_2020 | nda | Covid'19 case datesets of countries (2020), where the data frame has 138 observations of 18 variables. | data.frame | 138 | 18 |
CWTS_2020 | nda | CWTS Leiden's University Ranking 2020 for all scientific fields, within the period of 2016-2019. 1176 observations (i.e., universities), and 42 variables (i.e., indicators). | data.frame | 1176 | 42 |
CrimesUSA1990.X | nda | Crimes in USA cities in 1990. Independent variables (X) | data.frame | 1994 | 123 |
CrimesUSA1990.Y | nda | Crimes in USA cities in 1990. Dependent variable (Y) | data.frame | 1994 | 1 |
GOVDB2020 | nda | Governmental and economic data of countries (2020), where the data frame has 138 observations of 2161 variables. | data.frame | 138 | 2161 |
I40_2020 | nda | NUTS2 regional development data (2020) of I4.0 readiness, where the data frame has 414 observations of 101 variables. | data.frame | 414 | 101 |
pisa_2006 | perccalc | Mathematics test scores of Spain, Germany and Estonia in the PISA 2006 test | data.frame | 25884 | 6 |
pisa_2012 | perccalc | Mathematics test scores of Spain, Germany and Estonia in the PISA 2012 test | data.frame | 35093 | 6 |
KrigingExampleData | LatticeKrig | Synthetic data for kriging examples | list | | |
equatorGrid | LatticeKrig | Data examples for the LatticeKrig Vignette | matrix | 4050 | 2 |
equatorGridValues | LatticeKrig | Data examples for the LatticeKrig Vignette | numeric | | |
equatorLocations | LatticeKrig | Data examples for the LatticeKrig Vignette | matrix | 450 | 2 |
equatorValues | LatticeKrig | Data examples for the LatticeKrig Vignette | numeric | | |
polarGrid | LatticeKrig | Data examples for the LatticeKrig Vignette | matrix | 4050 | |
polarGridValues | LatticeKrig | Data examples for the LatticeKrig Vignette | numeric | | |
polarLocations | LatticeKrig | Data examples for the LatticeKrig Vignette | matrix | 450 | |
polarValues | LatticeKrig | Data examples for the LatticeKrig Vignette | numeric | | |
australia | simts | Quarterly Increase in Stocks Non-Farm Total, Australia | tbl_df | 127 | 2 |
hydro | simts | Mean Monthly Precipitation, from 1907 to 1972 | ts | | |
savingrt | simts | Personal Saving Rate | gts | 691 | 1 |
BD | smfsb | Example SPN models | list | | |
Dimer | smfsb | Example SPN models | list | | |
ID | smfsb | Example SPN models | list | | |
LV | smfsb | Example SPN models | list | | |
LVV | smfsb | Example SPN models | list | | |
LVirregular | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | matrix | 6 | 2 |
LVirregularNoise10 | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | matrix | 6 | 2 |
LVnoise10 | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | mts | 16 | 2 |
LVnoise10Scale10 | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | mts | 16 | 2 |
LVnoise30 | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | mts | 16 | 2 |
LVnoise3010 | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | mts | 16 | 2 |
LVperfect | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | mts | 16 | 2 |
LVprey | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | ts | | |
LVpreyNoise10 | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | ts | | |
LVpreyNoise10Scale10 | smfsb | Example simulated time courses from a stochastic Lotka-Volterra model | ts | | |
MM | smfsb | Example SPN models | list | | |
SEIR | smfsb | Example SPN models | list | | |
SIR | smfsb | Example SPN models | list | | |
mytable | smfsb | Simple example data frame | data.frame | 6 | 3 |
furseals | bisque | Data from a capture-recapture study of fur seal pups | data.frame | 7 | 3 |
R_example | unusualprofile | An example correlation matrix | matrix | 8 | 8 |
d_example | unusualprofile | An example data.frame | tbl_df | 1 | 8 |
Sachs | GGMncv | Data: Sachs Network | data.frame | 7466 | 11 |
bfi | GGMncv | Data: 25 Personality items representing 5 factors | data.frame | 2800 | 27 |
ptsd | GGMncv | Data: Post-Traumatic Stress Disorder | data.frame | 221 | 20 |
dji30retw | rmgarch | data: Dow Jones 30 Constituents Closing Value log Weekly Return | data.frame | 1141 | 30 |
dd_land | ggOceanMaps | Decimal degree land shapes | sf | 2806 | 4 |
dd_rbathy | ggOceanMaps | Decimal degree bathymetry | bathyRaster | | |
fdir_main_areas | ggOceanMaps | Major fisheries areas (hovedomraade) of Norway | sf | 75 | 2 |
fdir_sub_areas | ggOceanMaps | Norwegian sub-areas (lokasjon) for commercial fishing | sf | 2107 | 3 |
ices_areas | ggOceanMaps | ICES Advisory Areas | sf | 66 | 4 |
LongData | HDJM | Simulated Longtidunal Data | data.frame | 48700 | 4 |
SurvData | HDJM | Simulated Survival Data | data.frame | 100 | 4 |
Missouri | CensSpatial | TCDD concentrations in Missouri (1971). | data.frame | 127 | 5 |
depth | CensSpatial | Depths of a geological horizon. | data.frame | 100 | 6 |
lplex | beadplexr | LEGENDplex example data | list | | |
simplex | beadplexr | Simulated beadplex data | list | | |
Data1 | SNFtool | Data1 | data.frame | 200 | 2 |
Data2 | SNFtool | Data2 | data.frame | 200 | 2 |
dataL | SNFtool | dataL | list | | |
label | SNFtool | Labels for dataL dataset | integer | | |
diet | xtune | Simulated diet data to predict weight loss | list | | |
example | xtune | An simulated example dataset | list | | |
example.multiclass | xtune | Simulated data with multi-categorical outcome | list | | |
gene | xtune | Simulated gene data to predict weight loss | list | | |
geno | TSDFGS | Genotype information | matrix | 404 | 404 |
subpop | TSDFGS | Sub-population information | character | | |
LDprofile | zalpha | Dataset containing an example LD profile | data.frame | 50 | 5 |
snps | zalpha | Dataset containing details on simulated SNPs | data.frame | 20 | 12 |
aHDLt | tightenBlock | Alcohol and HDL Cholesterol | data.frame | 1624 | 14 |
ibmspko | MTS | Monthly simple returns of the stocks of International Business Machines (IBM) and Coca Cola (KO) and the S&P Composite index (SP) | data.frame | 612 | 4 |
qgdp | MTS | Quarterly real gross domestic products of United Kingdom, Canada, and the United States | data.frame | 126 | 5 |
tenstocks | MTS | Monthly simple returns of ten U.S. stocks | data.frame | 132 | 11 |
dataset.test | fscaret | Example testing data set | data.frame | 7 | 30 |
dataset.train | fscaret | Example training data set | data.frame | 61 | 30 |
funcClassPred | fscaret | Classification methods used. | character | | |
funcRegPred | fscaret | All regression methods used | character | | |
requiredPackages | fscaret | requiredPackages | character | | |
multivrealdataset | samurais | Time series representing the three acceleration components recorded over time with body mounted accelerometers during the activity of a given person. | data.frame | 2253 | 4 |
multivtoydataset | samurais | A simulated non-stationary multidimensional time series with regime changes. | data.frame | 670 | 4 |
univrealdataset | samurais | Time series representing the electrical power consumption during a railway switch operation | data.frame | 562 | 3 |
univtoydataset | samurais | A simulated non-stationary time series with regime changes. | data.frame | 670 | 2 |
X.varx | bigtime | VARX Time Series Example ('varx.example') | matrix | 200 | 3 |
Y.var | bigtime | VAR Time Series Example ('var.example') | matrix | 200 | 5 |
Y.varma | bigtime | VARMA Time Series Example ('varma.example') | matrix | 200 | 3 |
Y.varx | bigtime | VARX Time Series Example ('varx.example') | matrix | 200 | 3 |
adult_demo | edgedata | Adult Demographic Factors - Table 9 | tbl_df | 90 | 6 |
adult_enroll_dur | edgedata | Adult Enrollment Duration Factors - Table 9 | tbl_df | 55 | 4 |
adult_group | edgedata | Adult HCC Grouping Factors - Table 9 | tbl_df | 90 | 4 |
adult_hcc | edgedata | Adult HCC Factors - Table 9 | tbl_df | 655 | 4 |
adult_interaction | edgedata | Adult Interaction Factors - Table 9 | tbl_df | 5 | 4 |
adult_rxc | edgedata | Adult Rx Condition Factors - Table 9 | tbl_df | 50 | 4 |
adult_rxc_hcc_inter | edgedata | Adult RXC/HCC Interaction Factors - Table 9 | tbl_df | 165 | 5 |
cc_hier | edgedata | Condition Category Hierarchies - Table 4 | tbl_df | 203 | 3 |
cc_int_h | edgedata | HCC to interaction group "H" mapping - Table 6 | tbl_df | 9 | 3 |
cc_int_m | edgedata | HCC to interaction group "M" mapping - Table 6 | tbl_df | | 3 |
cc_severe | edgedata | HCC to severity group mapping - Table 6 | tbl_df | 8 | 3 |
child_demo | edgedata | Child Demographic Factors - Table 9 | tbl_df | 40 | 6 |
child_group | edgedata | Child HCC Grouping Factors - Table 9 | tbl_df | 105 | 4 |
child_hcc | edgedata | Child HCC Factors - Table 9 | tbl_df | 650 | 4 |
cpt_hcpcs | edgedata | RA-eligible CPT and HCPCS - Table 2 | tbl_df | 6594 | 5 |
hcpcs_rxc | edgedata | HCPCS to Rx Condition Crosswalk - Table 10b | tbl_df | 35 | 3 |
icd_cc | edgedata | ICD to Condition Category Crosswalk - Table 3 | tbl_df | 11755 | 11 |
infant_demo | edgedata | Infant Demographic Factors - Table 9 | tbl_df | 10 | 5 |
infant_mat_sev | edgedata | Infant Maturity/Severity Factors - Table 9 | tbl_df | 125 | 5 |
ndc_rxc | edgedata | NDC to Rx Condition Crosswalk - Table 10a | tbl_df | 11597 | 3 |
rxc_hier | edgedata | Rx Condition Hierarchies - Table 11 | tbl_df | 1 | 3 |
BigCity | BayesSampling | Full Person-level Population Database | data.frame | 150266 | 12 |
samp.A | StatMatch | Artificial data set resembling EU-SILC survey | data.frame | 3009 | 13 |
samp.B | StatMatch | Artificial data set resembling EU-SILC survey | data.frame | 6686 | 12 |
samp.C | StatMatch | Artificial data set resembling EU-SILC survey | data.frame | 980 | 14 |
doveData | DOVE | Toy Dataset For Illustration | data.frame | 40000 | 7 |
degs_lists | TOmicsVis | Paired comparisons differentially expressed genes (degs) among groups. | data.frame | 2447 | 4 |
degs_stats | TOmicsVis | All DEGs of paired comparison CT-vs-LT12 stats dataframe. | data.frame | 525 | 4 |
degs_stats2 | TOmicsVis | All DEGs of paired comparison CT-vs-LT12 stats2 dataframe. | data.frame | 525 | 4 |
gene_expression | TOmicsVis | All genes in all samples expression dataframe of RNA-Seq. | data.frame | 11033 | 16 |
gene_expression2 | TOmicsVis | Shared DEGs of all paired comparisons in all samples expression dataframe of RNA-Seq. | data.frame | 139 | 16 |
gene_expression3 | TOmicsVis | Shared DEGs of all paired comparisons in all groups expression dataframe of RNA-Seq. | data.frame | 139 | 7 |
gene_go_kegg | TOmicsVis | GO and KEGG annotation of background genes. | data.frame | 1280 | 5 |
gene_go_kegg2 | TOmicsVis | GO and KEGG annotation of background genes. | data.frame | 3840 | 4 |
network_data | TOmicsVis | Network data from WGCNA tan module top-200 dataframe. | data.frame | 200 | 2 |
samples_groups | TOmicsVis | Samples and groups for gene expression. | data.frame | 15 | 2 |
survival_data | TOmicsVis | Survival data as example data for survival_plot function. | data.frame | 200 | 3 |
traits_sex | TOmicsVis | Length, Width, Weight, and Sex traits dataframe. | data.frame | 600 | 3 |
weight_sex | TOmicsVis | Weight and Sex traits dataframe. | data.frame | 200 | 2 |
faceratings | faux | Attractiveness ratings of faces | tbl_df | 256326 | 9 |
fr4 | faux | Attractiveness rating subset | tbl_df | 768 | 9 |
GDPsatis | robCompositions | GDP satisfaction | data.frame | 31 | 8 |
ageCatWorld | robCompositions | child, middle and eldery population | data.frame | 195 | 4 |
alcohol | robCompositions | alcohol consumptions by country and type of alcohol | data.frame | 193 | 6 |
alcoholreg | robCompositions | regional alcohol per capita (15+) consumption by WHO region | data.frame | 6 | 4 |
arcticLake | robCompositions | arctic lake sediment data | data.frame | 39 | 3 |
cancer | robCompositions | hospital discharges on cancer and distribution of age | data.frame | 24 | 6 |
cancerMN | robCompositions | malignant neoplasms cancer | data.frame | 35 | 5 |
chorizonDL | robCompositions | C-horizon of the Kola data with rounded zeros | data.frame | 606 | 62 |
coffee | robCompositions | coffee data set | data.frame | 30 | 7 |
economy | robCompositions | economic indicators | data.frame | 30 | 7 |
educFM | robCompositions | education level of father (F) and mother (M) | data.frame | 31 | 7 |
efsa | robCompositions | efsa nutrition consumption | data.frame | 87 | 22 |
election | robCompositions | election data | data.frame | 16 | 8 |
electionATbp | robCompositions | Austrian presidential election data | data.frame | 2202 | 11 |
employment | robCompositions | employment in different countries by gender and status. | array | | |
employment2 | robCompositions | Employment in different countries by Sex, Age, Contract, Value | data.frame | 504 | 5 |
employment_df | robCompositions | Employment in different countries by gender and status. | data.frame | 132 | 4 |
expenditures | robCompositions | synthetic household expenditures toy data set | data.frame | 20 | 5 |
expendituresEU | robCompositions | mean consumption expenditures data. | data.frame | 27 | 12 |
foodbalance | robCompositions | country food balances | data.frame | 184 | 116 |
gemas | robCompositions | GEMAS geochemical data set | data.frame | 2108 | 30 |
gjovik | robCompositions | gjovik | data.frame | 615 | 63 |
govexp | robCompositions | government spending | data.frame | 5140 | 4 |
haplogroups | robCompositions | haplogroups data. | data.frame | 38 | 12 |
honey | robCompositions | honey compositions | data.frame | 429 | 17 |
instw | robCompositions | value added, output and input for different ISIC codes and countries. | data.frame | 1555 | 7 |
isic32 | robCompositions | ISIC codes by name | data.frame | 24 | 2 |
laborForce | robCompositions | labour force by status in employment | data.frame | 124 | 9 |
landcover | robCompositions | European land cover | data.frame | 28 | 7 |
lifeExpGdp | robCompositions | life expectancy and GDP (2008) for EU-countries | data.frame | 27 | 9 |
machineOperators | robCompositions | machine operators | data.frame | 27 | 4 |
manu_abs | robCompositions | Distribution of manufacturing output | data.frame | 630 | 4 |
mcad | robCompositions | metabolomics mcad data set | data.frame | 50 | 279 |
mortality | robCompositions | mortality and life expectancy in the EU | data.frame | 60 | 12 |
mortality_tab | robCompositions | mortality table | table | 8 | 2 |
nutrients | robCompositions | nutrient contents | tbl_df | 965 | 50 |
nutrients_branded | robCompositions | nutrient contents (branded) | data.frame | 9618 | 18 |
payments | robCompositions | special payments | data.frame | 535 | 11 |
phd | robCompositions | PhD students in the EU | data.frame | 31 | 11 |
phd_totals | robCompositions | PhD students in the EU (totals) | data.frame | 28 | 5 |
precipitation | robCompositions | 24-hour precipitation | matrix | 6 | 4 |
production | robCompositions | production splitted by nationality on enterprise level | data.frame | 535 | 9 |
rcodes | robCompositions | codes for UNIDO tables | data.frame | 2717 | 6 |
saffron | robCompositions | saffron compositions | data.frame | 53 | 36 |
skyeLavas | robCompositions | aphyric skye lavas data | data.frame | 23 | 3 |
socExp | robCompositions | social expenditures | data.frame | 20 | 8 |
teachingStuff | robCompositions | teaching stuff | data.frame | 1216 | 4 |
trondelagC | robCompositions | regional geochemical survey of soil C in Norway | data.frame | 754 | 70 |
trondelagO | robCompositions | regional geochemical survey of soil O in Norway | data.frame | 756 | 73 |
unemployed | robCompositions | unemployed of young people | data.frame | 5459 | 4 |
centenarian | depend.truncation | Japanese Centenarians Data | data.frame | 21 | 19 |
insem | Sunclarco | Insemination Data | data.frame | 10513 | 5 |
Biom | RankProd | Metabolomics data on spiked apples | numeric | | |
apples.cl | RankProd | Metabolomics data on spiked apples | numeric | | |
apples.data | RankProd | Metabolomics data on spiked apples | AsIs | 197 | 20 |
apples.data.vsn | RankProd | Metabolomics data on spiked apples | matrix | 197 | 20 |
arab | RankProd | Genomic Response to Brassinosteroid in Arabidopsis | matrix | 500 | 10 |
arab.cl | RankProd | Genomic Response to Brassinosteroid in Arabidopsis | numeric | | |
arab.gnames | RankProd | Genomic Response to Brassinosteroid in Arabidopsis | character | | |
arab.origin | RankProd | Genomic Response to Brassinosteroid in Arabidopsis | numeric | | |
golub | RankProd | A subset of the Gene expression dataset from Golub et al. (1999) | matrix | 500 | |
golub.cl | RankProd | A subset of the Gene expression dataset from Golub et al. (1999) | numeric | | |
golub.gnames | RankProd | A subset of the Gene expression dataset from Golub et al. (1999) | matrix | 500 | |
lym.exp | RankProd | Subset of the Intensity data for 8 cDNA slides with CLL and DLBL samples from the Alizadeh et al. paper in Nature 2000 | matrix | 500 | 16 |
mz | RankProd | Metabolomics data on spiked apples | numeric | | |
rt | RankProd | Metabolomics data on spiked apples | numeric | | |
Cats | bfw | Dataset with Cats | data.frame | 2000 | 4 |
rawDrugNamesCoOcEPILONT | epos | List drug terms with their frequency co-occurring with terms from the EPILONT ontology in publications since 2015 from the BioASQ 2020 corpus. | character | | |
rawDrugNamesCoOcEPISEM | epos | List drug terms with their frequency co-occurring with terms from the EPISEM ontology in publications since 2015 from the BioASQ 2020 corpus. | character | | |
rawDrugNamesCoOcESSO | epos | List drug terms with their frequency co-occurring with terms from the ESSO ontology in publications since 2015 from the BioASQ 2020 corpus. | character | | |
rawDrugNamesCoOcEpSO | epos | List drug terms with their frequency co-occurring with terms from the EpSO ontology in publications since 2015 from the BioASQ 2020 corpus. | character | | |
rawDrugNamesCoOcFENICS | epos | List drug terms with their frequency co-occurring with terms from the FENICS ontology in publications from the BioASQ 2020 corpus. | character | | |
matrices | ggtilematrix | | list | | |
triples | ggtilematrix | | list | | |
HNP | RRHO | RRHO comparison data sets. | data.frame | 15144 | 2 |
My | RRHO | RRHO comparison data sets. | data.frame | 15144 | 2 |
Sestan | RRHO | RRHO comparison data sets. | data.frame | 15144 | 2 |
test_data | multiROC | Example dataset | data.frame | 85 | 9 |
ImbC | UBL | Synthetic Imbalanced Data Set for a Multi-class Task | data.frame | 1000 | 3 |
ImbR | UBL | Synthetic Regression Data Set | data.frame | 1000 | 3 |
counts | DoubleExpSeq | Exon Inclusion Counts | matrix | 4000 | 15 |
groups | DoubleExpSeq | Group Structure of the Toy Data Set | character | | |
offsets | DoubleExpSeq | Exon Total Counts | matrix | 4000 | 15 |
sampledata | relcircle | Sample Data | data.frame | 74 | 10 |
coriell | DNAcopy | Array CGH data set of Coriell cell lines | data.frame | 2271 | 5 |
cytoBand | DNAcopy | Cytogenic band data | data.frame | 862 | 5 |
default.DNAcopy.bdry | DNAcopy | Sequential stopping boundary | integer | | |
ABAB | SCRT | Hypothetical ABAB data | data.frame | 24 | 2 |
data | pqrBayes | simulated data for demonstrating the features of pqrBayes | list | | |
DNAJC1 | GCPBayes | Gene DNAJC1 from BCAC and Epithyr studies | list | | |
PARP2 | GCPBayes | Gene PARP2 from CECILE study | list | | |
PARP2_summary | GCPBayes | Summary statistics of gene PARP2 from CECILE study | list | | |
Simulated_individual | GCPBayes | Simulated individual level data | list | | |
Simulated_individual_survival | GCPBayes | Simulated individual level survival data | list | | |
Simulated_summary | GCPBayes | Simulated summary statistics for K=5 traits | list | | |
data.check | SoyNAM | Datasets | data.frame | 9043 | 18 |
data.check.in | SoyNAM | Datasets | data.frame | 1650 | 21 |
data.check.qa | SoyNAM | Datasets | data.frame | 10721 | 11 |
data.line | SoyNAM | Datasets | data.frame | 60744 | 18 |
data.line.in | SoyNAM | Datasets | data.frame | 12790 | 21 |
data.line.qa | SoyNAM | Datasets | data.frame | 62572 | 11 |
gen.in | SoyNAM | Datasets | matrix | 5555 | 4240 |
gen.qa | SoyNAM | Datasets | matrix | 5180 | 4312 |
gen.raw | SoyNAM | Datasets | matrix | 5590 | 4611 |
colonexample | YPmodelPhreg | An example from Chemotherapy for Stage B/C colon cancer | data.frame | 619 | 6 |
sunspots_births | rotasym | Recorded sunspots births during 1872-2018 | data.frame | 51303 | 6 |
brown72 | pracma | Brownian Motion | numeric | | |
titanium | pracma | Titanium Test Data | data.frame | 49 | 2 |
SBB | recmap | jss2711 data | recmapGA | | |
Switzerland | recmap | jss2711 data | recmapGA | | |
UK | recmap | jss2711 data | recmapGA | | |
cmp_GA_GRASP | recmap | jss2711 data | list | | |
mbb_check | recmap | jss2711 data | data.frame | 11400 | 6 |
canva_palettes | ggthemes | 150 Color Palettes from Canva | list | | |
ggthemes_data | ggthemes | Palette and theme data | list | | |
lalonde | randChecks | Lalonde (1986) Data | data.frame | 614 | 9 |
lalonde.matched.card | randChecks | A Cardinality Matched Dataset for the Lalonde (1986) Data | data.frame | 240 | 10 |
lalonde.matched.ps | randChecks | A 1:1 Propensity Score Matched Dataset for the Lalonde (1986) Data | data.frame | 370 | 10 |
gadarian | stm | Gadarian and Albertson data | data.frame | 341 | 4 |
gadarianFit | stm | Gadarian and Albertson data | STM | | |
poliblog5k.docs | stm | CMU 2008 Political Blog Corpus | list | | |
poliblog5k.meta | stm | CMU 2008 Political Blog Corpus | data.frame | 5000 | 4 |
poliblog5k.voc | stm | CMU 2008 Political Blog Corpus | character | | |
hepatitisA | curstatCI | Hepatitis A data | data.frame | 83 | 3 |
rubella | curstatCI | Rubella data | data.frame | 225 | 3 |
crimes | rcrimeanalysis | Example data from the Chicago Data Portal | spec_tbl_df | 25000 | 22 |
BHS | simexaft | Busselton Health Study | data.frame | 100 | 18 |
rhDNase | simexaft | rhDNase Data Set | data.frame | 641 | 11 |
SMI | MSGARCH | Swiss market index dataset | zoo | | |
dem2gbp | MSGARCH | DEM/GBP exchange rate log-returns | numeric | | |
novelforest_data | novelforestSG | Novel Forest Raw Dataset | list | | |
TracksCleaned | movegroup | Data: Tracks of lemon sharks off Bimini, Bahamas | data.frame | 1308 | 5 |
argosFiltered | movegroup | Data: Tracks of two great hammerhead sharks with position confidence intervals | data.frame | 1492 | 8 |
bridge | emuR | Three-columned matrix | matrix | 13 | 3 |
coutts | emuR | Segment list of words, read speech, female speaker of Australian English from database epgcoutts | emusegs | 4 | 4 |
coutts.epg | emuR | EPG-compressed trackdata from the segment list coutts | trackdata | | |
coutts.l | emuR | Vector of word label from the segment list coutts | AsIs | | |
coutts.rms | emuR | rms Data to coutts segment list | trackdata | | |
coutts.sam | emuR | Trackdata of acoustic waveforms from the segment list coutts | trackdata | | |
coutts2 | emuR | Segment list, same as coutts but at a slower speech rate | emusegs | 4 | 4 |
demo.all | emuR | Emu segment list | emusegs | 28 | 4 |
demo.all.rms | emuR | Emu track data for a rms track for segment list demo.all | trackdata | | |
demo.vowels | emuR | Emu segment List | emusegs | 6 | 4 |
demo.vowels.f0 | emuR | F0 track data for segment list demo.vowels | trackdata | | |
demo.vowels.fm | emuR | Formant track data for segment list demo.vowels | trackdata | | |
dip | emuR | Segment list of diphthongs, two speakers one male, one female , Standard North German, read speech from database kielread | emusegs | 186 | 4 |
dip.fdat | emuR | Trackdata of formants from the segment list dip | trackdata | | |
dip.l | emuR | Vector of phoneme labels from the segment list dip | AsIs | | |
dip.spkr | emuR | Vector of speaker labels from the segment list dip | AsIs | | |
e.dft | emuR | Spectral vector of a single E vowel produced by a male speaker of Standard North German. | numeric | | |
engassim | emuR | Segment list of a sequence of syllable final n or N preceding k or g , isolated words single speaker, Australian English female from database epgassim. | emusegs | 32 | 4 |
engassim.epg | emuR | EPG-compressed trackdata from the segment list engassim | trackdata | | |
engassim.l | emuR | Vector of phonetic labels from the segment list engassim: nK = nk,ng , sK = sk,sg | character | | |
engassim.w | emuR | Vector of word labels from the segment list engassim. | character | | |
fric | emuR | Segment list of word-medial s or z one male speaker of Standard North German, read speech from database kielread. | emusegs | 34 | 4 |
fric.dft | emuR | Spectral trackdata object from the segment list fric. | trackdata | | |
fric.l | emuR | Vector of labels from the segment list fric | AsIs | | |
fric.w | emuR | Vector of word labels from the segment list fric. | character | | |
isol | emuR | Segment list of vowels in a d d context isolated word speech, one male speaker of Australian English from database isolated. | emusegs | 13 | 4 |
isol.fdat | emuR | Trackdata of formants from the segment list isol | trackdata | | |
isol.l | emuR | Vector of vowel phoneme labels from the segment list isol | AsIs | | |
polhom | emuR | Segment list of four Polish homorganic fricatives from database epgpolish. | emusegs | 40 | 4 |
polhom.epg | emuR | EPG-compressed trackdata from the segment list polhom | trackdata | | |
polhom.l | emuR | Vector of phonetic labels from the segment list polhom | AsIs | | |
vowlax | emuR | Segment list of four lax vowels, read speech, one male and one female speaker of Standard North German from database kielread. | emusegs | 410 | 4 |
vowlax.df | emuR | Data frame of various parameters and labels from the segment list vowlax | data.frame | 410 | 9 |
vowlax.dft.5 | emuR | Spectral matrix centred at the temporal midpoint of the vowels from the segment list vowlax. | matrix | 410 | 129 |
vowlax.fdat | emuR | Trackdata of formants from the segment list vowlax | trackdata | | |
vowlax.fdat.5 | emuR | Matrix of formant data extracted at the temporal midpoint from the segment list vowlax. | matrix | 410 | 4 |
vowlax.fund | emuR | Trackdata of fundamental frequency from the segment list vowlax | trackdata | | |
vowlax.fund.5 | emuR | Vector of fundamental frequency extracted at the temporal midpoint from the segment list vowlax. | numeric | | |
vowlax.l | emuR | Vector of phoneme labels from the segment list vowlax | AsIs | | |
vowlax.left | emuR | Vector of labels preceding the vowels from the segment list vowlax | character | | |
vowlax.right | emuR | Vector of labels following the vowels from the segment list vowlax | character | | |
vowlax.rms | emuR | Trackdata of RMS energy from the segment list vowlax | trackdata | | |
vowlax.rms.5 | emuR | Vector of RMS energy values at the temporal midpoint extracted at the temporal midpoint from the segment list vowlax | numeric | | |
vowlax.spkr | emuR | Vector of speaker labels from the segment list vowlax. | character | | |
vowlax.word | emuR | Vector of word labels from the segment list vowlax. | character | | |
dilution.phenodata | affycomp | Phenotypic Information for Dilution Study | AnnotatedDataFrame | | |
hgu133a.spikein.phenodata | affycomp | phenotypic information for HGU133A spike in study | AnnotatedDataFrame | | |
hgu133a.spikein.xhyb | affycomp | Cross hybridizers | list | | |
mas5.assessment | affycomp | Example of the result of assessments | list | | |
spikein.phenodata | affycomp | phenotypic information for spike in study | AnnotatedDataFrame | | |
MPINetData | famat | The variables in the environment variable 'MPINetData' of the system | environment | | |
compl_data_result | famat | Output of 'compl_data' function | list | | |
genes | famat | List of genes. | character | | |
interactions_result | famat | Output of 'interactions' function | list | | |
listk | famat | Pathway enrichment analysis results for KEGG pathways. | list | | |
listr | famat | Pathway enrichment analysis results for Reactome pathways. | list | | |
listw | famat | Pathway enrichment analysis results for Wikipathways pathways. | list | | |
meta | famat | List of metabolites. | character | | |
Depression | QDComparison | Jackson's CESD Depression Scores | data.frame | 372 | 2 |
Earnings1978 | QDComparison | LaLonde's 1978 Earnings Data | data.frame | 445 | 2 |
Fundraising | QDComparison | Gneezy's Fundraising Data with a Gift Wage | data.frame | 23 | 2 |
Microfinance | QDComparison | Informal Borrowing in Neighborhoods of Hyderabad, India | data.frame | 6811 | 2 |
NMES | QDComparison | National Medicare Expenditure Survey (NMES) Data on Cost of Hospitalizations | data.frame | 9416 | 2 |
diabetes | l2boost | Blood and other measurements in diabetics [Hastie and Efron (2012)] | list | | |
amExample1 | amregtest | Example 1 High quality data set | data.frame | 20 | 22 |
amExample2 | amregtest | Example 2 Good quality data set | data.frame | 148 | 22 |
amExample3 | amregtest | Example 3 Marginal quality data set | data.frame | 319 | 22 |
amExample4 | amregtest | Example 4 Low quality data set | data.frame | 307 | 22 |
amExample5 | amregtest | Example 5 Wildlife data set | data.frame | 335 | 23 |
ggSample | amregtest | Data sets originating from GG work | data.frame | 1658 | 187 |
AgencyUX | hcidata | Sense of Agency and User Experience | tbl_df | 126 | 26 |
CasualSteering | hcidata | Casual Interaction Steering Study | spec_tbl_df | 84 | 6 |
HafniaHands | hcidata | Hafnia Hands study on presence with different hand textures in virtual reality | list | | |
HandSize | hcidata | Touch Performance by Hand Size | list | | |
OccludedInteraction | hcidata | Acquisition study for occluded interaction | list | | |
VrPointing | hcidata | Pointing in Virtual Reality | list | | |
LPP2005REC | timeSeries | Time series data sets | timeSeries | 377 | 9 |
MSFT | timeSeries | Time series data sets | timeSeries | 249 | 5 |
USDCHF | timeSeries | Time series data sets | timeSeries | 62496 | 1 |
Property | DIFM | Property crime in United States | data.frame | 60 | 11 |
Violent | DIFM | Violent crime data in United States | data.frame | 60 | 11 |
WestStates | DIFM | Westen states in United States | SpatialPolygonsDataFrame | | |
COVID19 | refund | The US weekly all-cause mortality and COVID19-associated deaths in 2020 | list | | |
DTI | refund | Diffusion Tensor Imaging: tract profiles and outcomes | data.frame | 382 | 9 |
DTI2 | refund | Diffusion Tensor Imaging: more fractional anisotropy profiles and outcomes | data.frame | 340 | 5 |
PEER.Sim | refund | Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function | data.frame | 400 | 4 |
Q | refund | Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function | matrix | 7 | |
cd4 | refund | Observed CD4 cell counts | matrix | 366 | 61 |
content | refund | The CONTENT child growth study | data.frame | 4405 | 10 |
gasoline | refund | Octane numbers and NIR spectra of gasoline | data.frame | 60 | 2 |
sofa | refund | SOFA (Sequential Organ Failure Assessment) Data | data.frame | 520 | 7 |
ITCdat | CBSr | Sample participant data from a binary intertemporal choice task (aka delay discounting task) | data.frame | 120 | 3 |
RCdat | CBSr | Sample participant data from a binary risky choice task (aka risk aversion task) | data.frame | 120 | 3 |
IndividualSample | healthequal | World Health Organization (WHO) | data.frame | 17848 | 10 |
NonorderedSample | healthequal | World Health Organization (WHO) | data.frame | 34 | 11 |
NonorderedSampleMultipleind | healthequal | World Health Organization (WHO) | data.frame | 71 | 11 |
OrderedSample | healthequal | World Health Organization (WHO) | data.frame | 5 | 11 |
OrderedSampleMultipleind | healthequal | World Health Organization (WHO) | data.frame | 10 | 11 |
car | bnclassify | Car Evaluation Data Set. | data.frame | 1728 | 7 |
voting | bnclassify | Congress Voting Data Set. | data.frame | 435 | 17 |
crps | extremeIndex | Observations of 6-h rainfall amount with CRPS values of 3 calibrated ensemble forecasts for one lead time across France. | matrix | 112221 | 4 |
indicators.ALL | oldr | RAM-OP Indicators Dataset - ALL | tbl_df | 192 | 138 |
indicators.FEMALES | oldr | RAM-OP Indicators Dataset - FEMALES | tbl_df | 113 | 138 |
indicators.MALES | oldr | RAM-OP Indicators Dataset - MALES | tbl_df | 79 | 138 |
testPSU | oldr | RAM-OP Population Dataset | tbl_df | 16 | 2 |
testSVY | oldr | RAM-OP Survey Dataset | tbl_df | 192 | 90 |
Dodgeram | approxmatch | Dodge ram pk 2500 data on side airbag (SAB) usage from 1995 to 2015 | data.frame | 6953 | 33 |
waterways | geomtextpath | A simple features data frame of three Scottish waterways | sf | 29 | 3 |
X | VIGoR | An example of SNP genotypes (explanatory variables) | matrix | 500 | |
Y | VIGoR | An example of response variables. | numeric | | |
Z | VIGoR | An example of fixed effects (explanatory variables) | matrix | 500 | |
data_types | flashr | Data types deck | data.frame | 21 | 5 |
vectors | flashr | Vectors deck | data.frame | 14 | 4 |
example_flocker_model_single | flocker | Example single-season flocker model | brmsfit | | |
risk76.1929 | GoFKernel | Inmigrants Exposed to Risk of Death | numeric | | |
exprwt_sumstats | INTACT | TWAS weights for a simulated gene. | numeric | | |
gene_set_list | INTACT | Simulated gene set list. | list | | |
ld_sumstats | INTACT | LD correlation matrix from a simulated data set. | matrix | 1500 | |
multi_simdat | INTACT | Simulated TWAS, PWAS, and pairwise colocalization summary data. | data.table | 1197 | 6 |
protwt_sumstats | INTACT | PWAS weights for a simulated gene. | numeric | | |
simdat | INTACT | Simulated TWAS and colocalization summary data. | data.frame | 1197 | 3 |
z_sumstats | INTACT | TWAS and PWAS z-score for a simulated gene. | matrix | 2 | |
algae.rd | respR | Oxygen production respirometry data | data.table | 1200 | 2 |
background_con.rd | respR | Background respirometry data (constant) | data.table | 20664 | 2 |
background_exp.rd | respR | Background respirometry data (exponential) | data.table | 20664 | 2 |
background_lin.rd | respR | Background respirometry data (linear) | data.table | 20664 | 2 |
flowthrough.rd | respR | Flowthrough respirometry data on the chiton, _Mopalia lignosa_ | data.table | 935 | 4 |
flowthrough_mult.rd | respR | Multi-column flowthrough respirometry data | data.table | 3740 | 15 |
flowthrough_sim.rd | respR | Flowthrough respirometry data with increasing background rate | data.table | 3740 | 4 |
intermittent.rd | respR | Respirometry data of the sea urchin, _Heliocidaris Erythrogramma_ | data.table | 4831 | 2 |
sardine.rd | respR | Respirometry data of the sardine, _Sardinops sagax_ | data.table | 7513 | 3 |
squid.rd | respR | Respirometry data of the squid, _Doryteuthis opalescens_ | data.table | 34120 | 2 |
urchins.rd | respR | Multi-column respirometry data of the sea urchin, _Heliocidaris Erythrogramma_, including background respiration | data.table | 271 | 19 |
zeb_intermittent.rd | respR | Respirometry data of a zebrafish, _Danio rerio_ | data.table | 79251 | 2 |
twolines | colocalization | A simulated 2-lines test data in 3D | data.frame | 426 | 4 |
MMN | permutes | ERP data from Jager (in prep.). See the vignettes for details. | data.frame | 22407 | 34 |
Arno | rrcov3way | Chemical composition of water in the main stream of Arno river | array | | |
Kojima.boys | rrcov3way | Parental behaviour in Japan | array | | |
Kojima.girls | rrcov3way | Parental behaviour in Japan | array | | |
amino | rrcov3way | Amino acids fluorescence data. | array | | |
dorrit | rrcov3way | Dorrit fluorescence data. | array | | |
elind | rrcov3way | OECD Electronics Industries Data | array | | |
girls | rrcov3way | Sempe girls' growth curves data | array | | |
ulabor | rrcov3way | Undeclared labor by region in Italy | array | | |
va3way | rrcov3way | Manufacturing value added by technology intensity for several years | array | | |
waterquality | rrcov3way | Water quality data in Wyoming, USA | array | | |
adf.example | adfExplorer | An example of an amigaDisk object | amigaDisk | | |
boot.block.code | adfExplorer | Minimal executable code for a bootblock | data.frame | 23 | 2 |
NAACproxydata | reslr | Relative Sea level example dataset | data.frame | 1715 | 8 |
Clomial1000 | Clomial | Pre-computed results of Clomial. | list | | |
breastCancer | Clomial | Breast cancer data for clonal decomposition. | list | | |
khanmiss | impute | Khan microarray data with random missing values | data.frame | 2309 | 65 |
lincs.kd | BayesKnockdown | LINCS L1000 Knockdown Example Dataset | matrix | 21 | |
grid_city_2020 | jpgrid | List of grid square codes by Japanese municipalities | tbl_df | 462915 | 6 |
MOD_RNA_DICT_MODOMICS | Modstrings | Modstrings internals | DFrame | | |
MOD_RNA_DICT_TRNADB | Modstrings | Modstrings internals | DFrame | | |
modsDNA | Modstrings | Modstrings internals | DFrame | | |
modsRNA | Modstrings | Modstrings internals | DFrame | | |
segData | cghMCR | The constructor for the cghMCR class | DNAcopy | | |
doschedaData | Doscheda | Peptide Intensity data set for Doscheda | data.frame | 21140 | 15 |
processedExample | Doscheda | Processed Peptide Intensity data set for Doscheda | ChemoProtSet | | |
dat | RTopper | A test dataset for the RTopper package | list | | |
fgsList | RTopper | A list of Functional Gene Set (FGS) to be used to run the examples in the RTopper package | list | | |
gseResultsSep | RTopper | A list of separated gene set enrichment p-values to be used to run the examples in the RTopper package | list | | |
intScores | RTopper | A list of genomic scores integrated across distinct data sets to be used to run the examples in the RTopper package | list | | |
pheno | RTopper | A test dataset for the RTopper package | data.frame | 95 | 2 |
sepScores | RTopper | A list of separate gene-to-phenotype association scores, obtained indipendently for each distinct data set to be used to run the examples in the RTopper package | list | | |
language_test | regtomean | Language Test in High School | data.frame | 8 | 9 |
data_sim_mirt | lvmcomp | Simulated dataset for multivariate item response theory model. | list | | |
data_sim_pcirt | lvmcomp | Simulated dataset for generalized partial credit model. | list | | |
rtte_obs_nm | vpc | Simulated RTTE data (1x) | data.frame | 573 | 6 |
rtte_sim_nm | vpc | Simulated RTTE data (100x) | data.frame | 2000000 | 7 |
simple_data | vpc | A small rich dataset | list | | |
dip1 | disprofas | Dissolution data of a reference and a test batch | data.frame | 12 | 10 |
dip2 | disprofas | Dissolution data of one reference batch and five test batches | data.frame | 72 | 8 |
dip3 | disprofas | Dissolution data of two different capsule formulations | data.frame | 24 | 6 |
dip4 | disprofas | Dissolution data of two different formulations | data.frame | 24 | 4 |
dip5 | disprofas | Fluid weights of drink cans | data.frame | 100 | 3 |
dip6 | disprofas | Dissolution data of a reference and a test batch | data.frame | 24 | 31 |
dip7 | disprofas | Parameter estimates of Weibull fit to individual dissolution profiles | data.frame | 48 | 5 |
dip8 | disprofas | Parameter estimates of Weibull fit to individual dissolution profiles | data.frame | 36 | 4 |
ExampleDb | scoper | | tbl_df | 2000 | 16 |
clusMat | Dune | A clustering matrix used to demonstrate the ari-merging process. | matrix | 100 | 5 |
nuclei | Dune | Cluster labels for a subset of the allen Smart-Seq nuclei dataset | data.frame | 1744 | 7 |
available_data | SUNGEO | Data availability through SUNGEO API | list | | |
cc_dict | SUNGEO | Country code dictionary | data.table | 8626 | 3 |
clea_deu2009 | SUNGEO | Constituency level results for lower chamber legislative elections, Germany 2009. | sf | 16 | 11 |
clea_deu2009_df | SUNGEO | Constituency level results for lower chamber legislative elections, Germany 2009. | data.frame | 16 | 12 |
clea_deu2009_pt | SUNGEO | Constituency level results for lower chamber legislative elections, Germany 2009. | sf | 16 | 11 |
gpw4_deu2010 | SUNGEO | Population count raster for Germany, 2010. | RasterLayer | | |
hex_05_deu | SUNGEO | Hexagonal grid for Germany. | sf | 257 | 4 |
highways_deu1992 | SUNGEO | Roads polylines for Germany, 1992 | sf | 1741 | 6 |
adapted_epitaxial | ggDoE | Adapted epitaxial layer experiment | tbl_df | 16 | 7 |
aliased_design | ggDoE | D-efficient minimal aliasing design for five factors in 12 runs | tbl_df | 12 | 5 |
girder_experiment | ggDoE | Girder experiment | tbl_df | 36 | 3 |
original_epitaxial | ggDoE | Original epitaxial layer experiment | tbl_df | 16 | 7 |
pulp_experiment | ggDoE | Reflectance Data, Pulp Experiment | tbl_df | 5 | 4 |
dates_by_isoyearweek | cstime | Dates of different days within isoyearweeks | data.table | 10436 | 12 |
nor_workdays_by_date | cstime | Norwegian workdays and holidays by date | data.table | 10958 | 7 |
nor_workdays_by_isoyearweek | cstime | Norwegian workdays and holidays by isoyearweek | data.table | 1565 | 4 |
wdbc | kdevine | Wisconsin Diagnostic Breast Cancer (WDBC) | data.frame | 569 | 31 |
bigBinSize | deltaCaptureC | Big bin size | numeric | | |
binnedDeltaPlot | deltaCaptureC | Plot of Binned Delta Counts | gg | | |
binnedDeltaSE | deltaCaptureC | Binned difference of mean capture-C counts between EScells and Neurons | RangedSummarizedExperiment | | |
binnedSummarizedExperiment | deltaCaptureC | Binned Capture-C counts of EScells and Neurons | RangedSummarizedExperiment | | |
deltaSE | deltaCaptureC | Difference of mean capture-C counts between EScells and Neurons | RangedSummarizedExperiment | | |
miniDeltaSE | deltaCaptureC | Difference of mean capture-C counts between EScells and Neurons | RangedSummarizedExperiment | | |
miniSE | deltaCaptureC | Capture-C counts of EScells and Neurons | RangedSummarizedExperiment | | |
miniSEDF | deltaCaptureC | Capture-C counts of EScells and Neurons | data.frame | 1909 | 7 |
numPermutations | deltaCaptureC | Number of permutations used in example permutation testing. | numeric | | |
pValue | deltaCaptureC | P-value | numeric | | |
plotTitle | deltaCaptureC | Title for delta capture-C plot | character | | |
regionOfInterest | deltaCaptureC | Region of interest surrounding the viewpoint | GRanges | | |
significanceType | deltaCaptureC | Type for testing significance | character | | |
significantRegions | deltaCaptureC | Regions of significant remodeling in example data | GRanges | | |
significantRegionsPlot | deltaCaptureC | A plot of the significant regions in the sample data. | gg | | |
smallBinSize | deltaCaptureC | Small Bin Size | numeric | | |
smallBins | deltaCaptureC | Small Bins | GRanges | | |
smallSetOfSmallBins | deltaCaptureC | Small Bins | GRanges | | |
smallerDeltaSE | deltaCaptureC | A subset of miniDeltaSE. | RangedSummarizedExperiment | | |
viewpointRegion | deltaCaptureC | Region surrounding the viewpoint | GRanges | | |
weightsExampleBins | deltaCaptureC | Weights example bins | GRanges | | |
weightsExampleGr | deltaCaptureC | Weights example | GRanges | | |
copyNumbersSegmented | ACE | Segmented data of two tumor samples | QDNAseqCopyNumbers | | |
exmplESet | CCPROMISE | Example of Conceptual Expression Set | ExpressionSet | | |
exmplGeneSet | CCPROMISE | Example of Conceptual Gene Annotation | GeneSetCollection | | |
exmplMSet | CCPROMISE | Example of Conceptual Methylation Set | ExpressionSet | | |
exmplPat | CCPROMISE | Example of Conceptual Phenotype Pattern Definition Set | data.frame | 3 | 3 |
geneLength | genomicInstability | Average length of human and mouse known genes | integer | | |
geneLength | genomicInstability | Average length of human and mouse known genes | integer | | |
genePosition | genomicInstability | Chromosomal coordinate of human and mouse known genes | data.frame | 25221 | 2 |
genePosition | genomicInstability | Chromosomal coordinate of human and mouse known genes | data.frame | 24116 | 2 |
TN2016 | LNPar | Number of employees in year 2016 in all the firms of the Trento district | integer | | |
classification_scheme | planttfhunter | Data frame of TF family classification scheme | data.frame | 58 | 5 |
gsu | planttfhunter | Protein sequences of the algae species Galdieria sulphuraria | AAStringSet | | |
gsu_annotation | planttfhunter | Domain annotation for the algae species Galdieria sulphuraria The data set was created using the funcion 'annotate_pfam()' in local mode. | data.frame | 449 | 2 |
gsu_families | planttfhunter | TFs families of the algae species Galdieria sulphuraria The data set was created using the funcion 'classify_tfs()'. | data.frame | 125 | 2 |
tf_counts | planttfhunter | TF counts per family in 4 simulated species | SummarizedExperiment | | |
data_land | PrInDT | Landscape analysis | data.frame | 149 | 24 |
data_speaker | PrInDT | Subject pronouns and a predictor with one very frequent level | data.frame | 3370 | 6 |
data_vowel | PrInDT | Vowel length | data.frame | 82 | 22 |
data_zero | PrInDT | Subject pronouns | data.frame | 1024 | 7 |
background_df | scPCA | Simulated Background Data for cPCA and scPCA | data.frame | 400 | 30 |
toy_df | scPCA | Simulated Target Data for cPCA and scPCA | data.frame | 400 | 31 |
cricket_batting | weird | Cricket batting data for international test players | tbl_df | 3754 | 15 |
fr_mortality | weird | French mortality rates by age and sex | tbl_df | 31648 | 4 |
n01 | weird | Multivariate standard normal data | tbl_df | 1000 | 10 |
oldfaithful | weird | Old faithful eruption data | tbl_df | 2261 | 3 |
example01 | lavacreg | A first example dataset to illustrate the use of lavacreg | data.frame | 871 | 9 |
chol_answers | TrajectoryGeometry | chol_answers | list | | |
chol_attributes | TrajectoryGeometry | chol_attributes | matrix | 229 | 10 |
chol_branch_point_results | TrajectoryGeometry | chol_branch_point_results | list | | |
chol_pseudo_time | TrajectoryGeometry | chol_pseudo_time | numeric | | |
chol_pseudo_time_normalised | TrajectoryGeometry | chol_pseudo_time_normalised | numeric | | |
crooked_path | TrajectoryGeometry | Crooked path | matrix | 14 | |
crooked_path_center | TrajectoryGeometry | Crooked path center | numeric | | |
crooked_path_projection | TrajectoryGeometry | Crooked path projection | matrix | 8 | |
crooked_path_radius | TrajectoryGeometry | Crooked path radius | numeric | | |
hep_answers | TrajectoryGeometry | hep_answers | list | | |
hep_attributes | TrajectoryGeometry | hep_attributes | matrix | 360 | 10 |
hep_pseudo_time | TrajectoryGeometry | hep_pseudo_time | numeric | | |
hep_pseudo_time_normalised | TrajectoryGeometry | hep_pseudo_time_normalised | numeric | | |
oscillation | TrajectoryGeometry | Oscillation | matrix | 20 | |
single_cell_matrix | TrajectoryGeometry | single_cell_matrix | matrix | 447 | 10 |
straight_path | TrajectoryGeometry | Straight path | matrix | 14 | |
straight_path_center | TrajectoryGeometry | Straight path center | numeric | | |
straight_path_projection | TrajectoryGeometry | Straight path projection | matrix | 13 | |
straight_path_radius | TrajectoryGeometry | Straight path radius | numeric | | |
gr | tRNA | tRNA example data | GRanges | | |
gr_eco | tRNA | tRNA example data | GRanges | | |
gr_human | tRNA | tRNA example data | GRanges | | |
gr_human2 | tRNA | tRNA example data | GRanges | | |
example_diff_result | pairedGSEA | Output of running paired_diff on example_se. | DFrame | | |
example_gene_sets | pairedGSEA | MSigDB gene sets from humans, category C5 with ensemble gene IDs | list | | |
example_ora_results | pairedGSEA | Output of running paired_ora on example_diff_result and gene sets extracted from MSigDB | DFrame | | |
example_se | pairedGSEA | A small subset of the GEO:GSE61220 data set. | SummarizedExperiment | | |
vac1.day0vs31.de.genes | RITAN | This dataset is included as an example in the package: | character | | |
vac1.day0vs56.de.genes | RITAN | This dataset is included as an example in the package: | character | | |
vac2.day0vs31.de.genes | RITAN | This dataset is included as an example in the package: | character | | |
vac2.day0vs56.de.genes | RITAN | This dataset is included as an example in the package: | character | | |
cod | tinyarray | cod | matrix | 100 | 512 |
deg | tinyarray | deg | data.frame | 18591 | 10 |
deseq_data | tinyarray | deseq_data | data.frame | 552 | 6 |
exists_anno_list | tinyarray | exists_anno_list | character | | |
exp_hub1 | tinyarray | exp_hub1 | matrix | 8 | 350 |
exprSet_hub1 | tinyarray | exprSet_hub1 | matrix | 8 | 177 |
genes | tinyarray | genes | character | | |
lnc_anno | tinyarray | lnc_anno | data.frame | 14826 | 3 |
lnc_annov23 | tinyarray | lnc_annov23 | data.frame | 14852 | 3 |
mRNA_anno | tinyarray | mRNA_anno | data.frame | 19814 | 3 |
mRNA_annov23 | tinyarray | mRNA_annov23 | data.frame | 19797 | 3 |
meta1 | tinyarray | meta1 | data.frame | 177 | 4 |
pkg_all | tinyarray | pkg_all | data.frame | 82 | 3 |
GSS | FactorCopula | The 1994 General Social Survey | data.frame | 464 | 7 |
PE | FactorCopula | Political-economic risk of 62 countries for the year 1987 | matrix | 62 | 5 |
PTSD | FactorCopula | The Post-traumatic stress disorder (PTSD) | matrix | 221 | 20 |
TAS | FactorCopula | Toronto Alexithymia Scale (TAS) | matrix | 1925 | 20 |
SNPhood.o | SNPhood | SNPhood example data | SNPhood | | |
CD4 | QRegVCM | The CD4 dataset | data.frame | 1817 | 6 |
wages | QRegVCM | The wages dataset | data.frame | 6402 | 7 |
toyCleanedAml | iNETgrate | A subset of cleaned TCGA-LAML data | list | | |
toyComputEloci | iNETgrate | A subset of weighted DNA methylation profile of TCGA-LAML data | list | | |
toyEigengenes | iNETgrate | A subset of weighted average of gene expression present in each module | matrix | 158 | 4 |
toyRawAml | iNETgrate | A subset of TCGA-LAML data | list | | |
chr20 | binhf | DNA datasets | numeric | | |
mhc | binhf | DNA datasets | numeric | | |
pintens | binhf | pintens | numeric | | |
LStraps | secr | Skink Pitfall Data | traps | 462 | 2 |
OVpossumCH | secr | Orongorongo Valley Brushtail Possums | capthist | | |
blackbearCH | secr | Black Bear Hair Snag Dataset | capthist | | |
captXY | secr | SECR Models Fitted to Demonstration Data | data.frame | 235 | 5 |
captdata | secr | SECR Models Fitted to Demonstration Data | capthist | | |
deermouse.ESG | secr | Deermouse Live-trapping Datasets | capthist | | |
deermouse.WSG | secr | Deermouse Live-trapping Datasets | capthist | | |
hornedlizardCH | secr | Flat-tailed Horned Lizard Dataset | capthist | | |
housemouse | secr | House mouse live trapping data | capthist | | |
infraCH | secr | Skink Pitfall Data | capthist | | |
lineoCH | secr | Skink Pitfall Data | capthist | | |
ovenCH | secr | Ovenbird Mist-netting Dataset | capthist | | |
ovenCHp | secr | Ovenbird Mist-netting Dataset | capthist | | |
ovenbird.model.1 | secr | Ovenbird Mist-netting Dataset | secr | | |
ovenbird.model.D | secr | Ovenbird Mist-netting Dataset | secr | | |
ovenmask | secr | Ovenbird Mist-netting Dataset | mask | | |
ovensong.model.1 | secr | Ovenbird Acoustic Dataset | secr | | |
ovensong.model.2 | secr | Ovenbird Acoustic Dataset | secr | | |
possum.model.0 | secr | Brushtail Possum Trapping Dataset | secr | | |
possum.model.Ds | secr | Brushtail Possum Trapping Dataset | secr | | |
possumCH | secr | Brushtail Possum Trapping Dataset | capthist | | |
possumarea | secr | Brushtail Possum Trapping Dataset | data.frame | 152 | 2 |
possummask | secr | Brushtail Possum Trapping Dataset | mask | 5120 | 2 |
possumremovalarea | secr | Brushtail Possum Trapping Dataset | data.frame | 116 | 2 |
secrdemo.0 | secr | SECR Models Fitted to Demonstration Data | secr | | |
secrdemo.CL | secr | SECR Models Fitted to Demonstration Data | secr | | |
secrdemo.b | secr | SECR Models Fitted to Demonstration Data | secr | | |
signalCH | secr | Ovenbird Acoustic Dataset | capthist | | |
stoat.model.EX | secr | Stoat DNA Data | secr | | |
stoat.model.HN | secr | Stoat DNA Data | secr | | |
stoatCH | secr | Stoat DNA Data | capthist | | |
trapXY | secr | SECR Models Fitted to Demonstration Data | data.frame | 100 | 3 |
demo_gate_data | tidygate | Demo gate data | tbl_df | 26 | 3 |
gate_list | tidygate | Example gate_list | list | | |
tidygate_data | tidygate | Example data set | spec_tbl_df | 2240 | 8 |
Airpollution | timsac | Airpollution Data | numeric | | |
Amerikamaru | timsac | Amerikamaru Data | matrix | 896 | |
Blsallfood | timsac | Blsallfood Data | numeric | | |
Canadianlynx | timsac | Time series of Canadian lynx data | numeric | | |
LaborData | timsac | Labor force Data | numeric | | |
Powerplant | timsac | Power Plant Data | matrix | 500 | |
bispecData | timsac | Univariate Test Data | numeric | | |
locarData | timsac | Non-stationary Test Data | numeric | | |
nonstData | timsac | Non-stationary Test Data | numeric | | |
Bus | ThreeWay | Bus data | matrix | 7 | 185 |
Kinship | ThreeWay | Kinship terms data | array | | |
TV | ThreeWay | TV data | list | | |
meaudret | ThreeWay | Meaudret data | array | | |
fpkm | RNAAgeCalc | An example of FPKM data | matrix | 24989 | 2 |
rawcount | RNAAgeCalc | An example of RNASeq counts data | matrix | 24989 | 2 |
basins_tehri | damAOI | Polygon for river basins around tehri dam | sf | 317 | 2 |
system | damAOI | Polygons for the 'Areas of Interest' around two dams which form a system together. | sf | 8 | 4 |
tehri | damAOI | Polygon for Tehri dam in India | sf | 1 | 2 |
bem_dfmdata | bvartools | FRED-QD data | mts | 225 | 196 |
e1 | bvartools | West German economic time series data | mts | 92 | 3 |
e6 | bvartools | German interest and inflation rate data | mts | 107 | 2 |
us_macrodata | bvartools | US macroeconomic data | mts | 195 | 3 |
Education | Indicator | Education | data.frame | 20 | 8 |
cpain | sanon | Chronic Pain Data | data.frame | 193 | 4 |
heartburn | sanon | Relief of heartburn Data | data.frame | 60 | 11 |
resp | sanon | Respiratory Disorder Data | data.frame | 111 | 9 |
sebor | sanon | Seborrheic Dermatitis Data | data.frame | 167 | 8 |
skin | sanon | Skin Condition Data | data.frame | 172 | 6 |
adults_06 | enseResp | | spec_tbl_df | 29478 | 619 |
adults_06_info | enseResp | | spec_tbl_df | 619 | 6 |
adults_06_labels | enseResp | | spec_tbl_df | 2328 | 2 |
adults_12 | enseResp | | spec_tbl_df | 21007 | 577 |
adults_12_info | enseResp | | tbl_df | 577 | 6 |
adults_12_labels | enseResp | | tbl_df | 2714 | 3 |
adults_19 | enseResp | adults_19 | spec_tbl_df | 23089 | 455 |
adults_19_info | enseResp | adults_19_info | tbl_df | 455 | 6 |
adults_19_labels | enseResp | | tbl_df | 2305 | 3 |
children_06 | enseResp | | spec_tbl_df | 9122 | 350 |
children_06_info | enseResp | | spec_tbl_df | 350 | 7 |
children_06_labels | enseResp | | spec_tbl_df | 1306 | 2 |
children_12 | enseResp | | spec_tbl_df | 5495 | 271 |
children_12_info | enseResp | | tbl_df | 271 | 6 |
children_12_labels | enseResp | | tbl_df | 1289 | 3 |
children_19 | enseResp | children_19 | spec_tbl_df | 6106 | 267 |
children_19_info | enseResp | children_19_info | tbl_df | 267 | 6 |
children_19_labels | enseResp | | tbl_df | 1310 | 3 |
house_06_labels | enseResp | | spec_tbl_df | 611 | 2 |
household_06 | enseResp | | spec_tbl_df | 85044 | 84 |
household_06_info | enseResp | | spec_tbl_df | 84 | 7 |
household_12 | enseResp | | spec_tbl_df | 55806 | 66 |
household_12_info | enseResp | | tbl_df | 66 | 6 |
household_12_labels | enseResp | | tbl_df | 269 | 3 |
household_19 | enseResp | household_19 | spec_tbl_df | 60143 | 58 |
household_19_info | enseResp | household_19_info | tbl_df | 58 | 6 |
household_19_labels | enseResp | | tbl_df | 312 | 3 |
regional_map | enseResp | | tbl_df | 40111 | 11 |
ex_binary | triptych | Example data set of binary observations and probability forecasts | tbl_df | 1000 | 11 |
eSet | epigenomix | Example gene expression data set. | ExpressionSet | | |
fpkm | epigenomix | Example RNA-seq data set. | data.frame | 3502 | 13 |
mappedReads | epigenomix | Mapped reads obtained from a anti-histone ChIP-seq experiment. | CompressedGRangesList | | |
transToTSS | epigenomix | A data frame with Ensemble transcript IDs and transcriptional start sites. | data.frame | 277 | 4 |
dataSimExample | methInheritSim | A 'list' containing methylation information used by some internal functions (for demo purpose. | list | | |
samplesForChrSynthetic | methInheritSim | All samples information, formated by 'methylKit', in a 'methylBase' format (for demo purpose). | methylBase | 9864 | 40 |
AIBS | rankrate | Real peer review data set from the American Institute of Biological Sciences (AIBS) | list | | |
ToyData1 | rankrate | Toy data set of rankings and ratings demonstrating tie-breaking | list | | |
ToyData2 | rankrate | Toy data set of rankings and ratings demonstrating decision-making with partial rankings | list | | |
ToyData3 | rankrate | Toy data set of rankings and ratings when judges express internally inconsistent preferences | list | | |
MOB_subset | scHOT | MOB_subset spatial example data | list | | |
liver | scHOT | Liver trajectory example data | list | | |
conversionFactors | omnibus | Data frame or conversion factors for length or areal units | data.frame | 100 | 3 |
domLeap | omnibus | Day of month for leap years | data.frame | 31 | 12 |
domNonLeap | omnibus | Day of month for non-leap years | data.frame | 31 | 12 |
doyLeap | omnibus | Day of year for leap years | data.frame | 31 | 12 |
doyNonLeap | omnibus | Days of year for non-leap years | data.frame | 31 | 12 |
sample_data | rciplot | Sample Data from Jacobson & Truax (1991) | data.frame | 30 | 3 |
crc.gr | biovizBase | CRC | GRanges | | |
crc1.GeRL | biovizBase | crc1.GeRL | SimpleGRangesList | | |
darned_hg19_subset500 | biovizBase | Subset of RNA editing sites in hg19... | GRanges | | |
genesymbol | biovizBase | Gene symbols with position... | GRanges | | |
hg19Ideogram | biovizBase | Hg19 ideogram without cytoband information... | GRanges | | |
hg19IdeogramCyto | biovizBase | Hg19 ideogram with cytoband information... | GRanges | | |
hg19sub | biovizBase | CRC | GRanges | | |
ideo | biovizBase | ideogram without cytoband information | list | | |
ideoCyto | biovizBase | ideogram with cytoband information | list | | |
mut.gr | biovizBase | CRC | GRanges | | |
rat | geneXtendeR | Gene transfer format (GTF) file for rat (Rattus_norvegicus.Rnor_6.0.84) | data.frame | 748514 | 28 |
samplepeaksinput | geneXtendeR | Sample peaks list to be used as input to geneXtendeR | data.table | 25089 | 3 |
CanadianWeather | fda | Canadian average annual weather cycle | list | | |
MontrealTemp | fda | Montreal Daily Temperature | matrix | 34 | 365 |
ReginaPrecip | fda | Regina Daily Precipitation | numeric | | |
daily | fda | Canadian average annual weather cycle | list | | |
day.5 | fda | Numeric and character vectors to facilitate working with dates | numeric | | |
dayOfYear | fda | Numeric and character vectors to facilitate working with dates | integer | | |
dayOfYearShifted | fda | Numeric and character vectors to facilitate working with dates | integer | | |
daysPerMonth | fda | Numeric and character vectors to facilitate working with dates | numeric | | |
gait | fda | Hip and knee angle while walking | array | | |
growth | fda | Berkeley Growth Study data | list | | |
handwrit | fda | Cursive handwriting samples | array | | |
handwritTime | fda | Cursive handwriting samples | numeric | | |
infantGrowth | fda | Tibia Length for One Baby | matrix | 40 | 3 |
lip | fda | Lip motion | matrix | 51 | |
lipmarks | fda | Lip motion | data.frame | 20 | 2 |
liptime | fda | Lip motion | numeric | | |
melanoma | fda | melanoma 1936-1972 | matrix | 37 | |
monthBegin.5 | fda | Numeric and character vectors to facilitate working with dates | numeric | | |
monthEnd | fda | Numeric and character vectors to facilitate working with dates | numeric | | |
monthEnd.5 | fda | Numeric and character vectors to facilitate working with dates | numeric | | |
monthLetters | fda | Numeric and character vectors to facilitate working with dates | character | | |
monthMid | fda | Numeric and character vectors to facilitate working with dates | numeric | | |
nondurables | fda | Nondurable goods index | numeric | | |
pinch | fda | pinch force data | matrix | 151 | |
pinchraw | fda | pinch force data | matrix | 151 | |
pinchtime | fda | pinch force data | numeric | | |
refinery | fda | Reflux and tray level in a refinery | data.frame | 194 | 3 |
seabird | fda | Sea Bird Counts | data.frame | 3793 | 22 |
weeks | fda | Numeric and character vectors to facilitate working with dates | numeric | | |
polymod_uk | finalsize | Example POLYMOD social contact data for the U.K. | list | | |
Pinus | QuESTr | Transcriptomes of Pinus roots under a Temperature Gradient | list | | |
icaSetCarbayo | MineICA | IcaSet-object containing a FastICA decomposition of gene expression microarrray-based data of bladder cancer samples. | IcaSet | | |
spdata | SpNMF | spdata | matrix | 80 | |
genes | goseq | Androgen stimulation of prostate cancer Cell lines. | integer | | |
ELEVATION | RMAWGEN | Trentino Dataset | array | | |
LOCATION | RMAWGEN | Trentino Dataset | array | | |
PRECIPITATION | RMAWGEN | Trentino Dataset | data.frame | 18262 | 62 |
PRECIPITATION_MEASUREMENT_END_DAY | RMAWGEN | Trentino Dataset | array | | |
PRECIPITATION_MEASUREMENT_START_DAY | RMAWGEN | Trentino Dataset | array | | |
STATION_LATLON | RMAWGEN | Trentino Dataset | matrix | 59 | |
STATION_NAMES | RMAWGEN | Trentino Dataset | array | | |
TEMPERATURE_MAX | RMAWGEN | Trentino Dataset | data.frame | 18262 | 62 |
TEMPERATURE_MEASUREMENT_END_DAY | RMAWGEN | Trentino Dataset | array | | |
TEMPERATURE_MEASUREMENT_START_DAY | RMAWGEN | Trentino Dataset | array | | |
TEMPERATURE_MIN | RMAWGEN | Trentino Dataset | data.frame | 18262 | 62 |
Access | ChIPanalyser | ChIPanalyserData | GRanges | | |
chip | ChIPanalyser | ChIPanalyserData | GRanges | | |
cs | ChIPanalyser | ChIPanalyserData | UCSCData | | |
geneRef | ChIPanalyser | ChIPanalyserData | GRanges | | |
top | ChIPanalyser | ChIPanalyserData | GRanges | | |
gol | CrispRVariants | Variant sequences from golden clutch 1 (Burger et al) | CrisprSet | | |
DKAP1061 | bayesvl | | data.frame | 970 | 188 |
Legends345 | bayesvl | Legends345 data | data.frame | 345 | 27 |
STEM5000 | bayesvl | | data.frame | 4018 | 43 |
data1042 | bayesvl | | data.frame | 1042 | 41 |
BLSALLFOOD | TSSS | BLSALLFOOD Data | ts | | |
HAKUSAN | TSSS | Ship's Navigation Data | mts | 1000 | 4 |
Haibara | TSSS | Haibara Data | mts | 400 | 2 |
MYE1F | TSSS | Seismic Data | ts | | |
NLmodel | TSSS | The Nonlinear State-Space Model Data | mts | 100 | 2 |
Nikkei225 | TSSS | Nikkei225 | ts | | |
PfilterSample | TSSS | Sample Data for Particle Filter and Smoother | ts | | |
Rainfall | TSSS | Rainfall Data | ts | | |
Sunspot | TSSS | Sunspot Number Data | ts | | |
Temperature | TSSS | Temperatures Data | ts | | |
WHARD | TSSS | Wholesale Hardware Data | ts | | |
altman | irrCAC | Dataset describing the Altman's Benchmarking Scale | data.frame | 5 | 3 |
cac.ben.gerry | irrCAC | Ratings of 12 units from 2 raters named Ben and Gerry | data.frame | 12 | 4 |
cac.dist.g1g2 | irrCAC | Distribution of 4 raters by subject and by category, for 14 Subjects that belong to 2 groups "G1" and "G2" | data.frame | 14 | 7 |
cac.dist4cat | irrCAC | Distribution of 4 raters by Category and Subject - Subjects allocated in 2 groups A and B. | data.frame | 15 | 4 |
cac.raw.g1g2 | irrCAC | Dataset of raw ratings from 4 Raters on 14 Subjects that belong to 2 groups named "G1" and "G2" | data.frame | 14 | 6 |
cac.raw.gender | irrCAC | Rating Data from 4 Raters and 15 human Subjects, 9 of whom are female and 6 males. | data.frame | 15 | 5 |
cac.raw4raters | irrCAC | Rating Data from 4 Raters and 12 Subjects. | data.frame | 12 | 4 |
cac.raw5obser | irrCAC | Scores assigned by 5 observers to 20 experimental units. | data.frame | 15 | 5 |
cont3x3abstractors | irrCAC | Distribution of 100 pregnant women by pregnancy type and by abstractor. | data.frame | 3 | 3 |
cont4x4diagnosis | irrCAC | Distribution of 223 Psychiatric Patients by Type of of Psychiatric Disorder and Diagnosis Method. | data.frame | 4 | 4 |
distrib.6raters | irrCAC | Distribution of 6 psychiatrists by Subject/patient and diagnosis Category. | data.frame | 15 | 5 |
fleiss | irrCAC | Dataset describing Fleiss' Benchmarking Scale | data.frame | 3 | 3 |
landis.koch | irrCAC | Dataset describing the Landis & Koch Benchmarking Scale | data.frame | 6 | 3 |
lik_data | ResIN | Likert-type simulated data for "ResIN" package examples | data.frame | 1000 | 12 |
calendar_properties | toastui | Calendar properties | data.frame | 6 | 3 |
countries | toastui | Information on population, region, area size, infant mortality and more. | data.frame | 227 | 20 |
met_paris | toastui | Meteorological for Le Bourget Station | data.frame | 12 | 3 |
ps3_games | toastui | Top 20 PS3 games | data.frame | 20 | 8 |
rolling_stones_50 | toastui | Rolling Stone's 50 Greatest Albums of All Time | data.frame | 50 | 6 |
rolling_stones_500 | toastui | Rolling Stone's 500 Greatest Albums of All Time | data.frame | 500 | 6 |
schedules_properties | toastui | Schedules properties | data.frame | 26 | 3 |
AHMD_sample | MortalityLaws | AHMD sample Data object generated by the 'ReadAHMD()' function. | ReadAHMD | | |
CHMD_sample | MortalityLaws | CHMD sample Data object generated by the 'ReadCHMD()' function. | ReadCHMD | | |
HMD_sample | MortalityLaws | HMD sample Data object generated by the 'ReadHMD()' function. | ReadHMD | | |
JMD_sample | MortalityLaws | JMD sample Data object generated by the 'ReadJMD()' function. | ReadJMD | | |
ahmd | MortalityLaws | MortalityLaws Test Data | list | | |
Firm | PLreg | Firm Cost | data.frame | 73 | 7 |
PeruVotes | PLreg | Peru Blank Votes | data.frame | 194 | 2 |
bodyfat_Aeolus | PLreg | Body Fat of Little Brown Bat | data.frame | 159 | 4 |
all_works_df | bardr | Contents of Complete Works of William Shakespeare (dataframe) | data.frame | 140804 | 4 |
all_works_list | bardr | Contents of Complete Works of William Shakespeare (list) | list | | |
BAdata | dMod | | data.frame | 228 | 8 |
jakstat | dMod | Time-course data for the JAK-STAT cell signaling pathway | data.frame | 47 | 5 |
dailydata | nser | Daily data of a stock | spec_tbl_df | 499 | 7 |
AEdata | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 66 | 5 |
AudiencePercent | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | matrix | 6 | 4 |
Design_2.8_2 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 64 | 2 |
Discrete4 | HH | Discrete with four levels color dataset. | character | | |
NZScienceTeaching | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 10 | 7 |
PoorChildren | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 6 | 5 |
ProfChal | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 16 | 7 |
ProfDiv | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | matrix | 7 | 4 |
R282 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 64 | 11 |
R282.y | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | numeric | | |
SFF8121 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | array | | |
abc | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 12 | 5 |
abrasion | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 30 | 3 |
acacia | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | table | 2 | 2 |
aeanonym | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 66 | 5 |
animal | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 3 |
anneal | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 36 | 4 |
apple | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 4 |
ara | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 277 | 6 |
balance | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 17 | 2 |
barleyp | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 3 |
batch | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 25 | 2 |
bean | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 4 |
birthweight | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 56 | 4 |
blood | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 2 |
blyth | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | matrix | 2 | 4 |
breast | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 16 | 2 |
budworm | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 12 | 3 |
byss | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 72 | 7 |
c3c4 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 194 | 2 |
catalystm | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 16 | 2 |
cc135 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 18 | 8 |
cc176 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 96 | 6 |
cement | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 13 | 5 |
census4 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 400 | 8 |
cereals | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 77 | 17 |
chimp | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 40 | 3 |
circuit | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 16 | 6 |
co2 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
col3x2 | HH | col3x2 color dataset | character | | |
concord | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 496 | 6 |
crash | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 12 | 3 |
crime | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | table | 6 | 2 |
darwin | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 15 | 2 |
diamond | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 2 |
display | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 4 |
distress | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 50 | 2 |
draft | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 372 | 3 |
draft70mn | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 31 | 12 |
drunk | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | table | 2 | 5 |
eggs | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 4 |
elnino | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
employM16 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
energy | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 88 | 6 |
esr | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 32 | 3 |
fabricwear | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 2 |
fat | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 47 | 5 |
fat.dat | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 252 | 19 |
feed | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 30 | 3 |
filmcoat | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 27 | 3 |
filter | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 36 | 4 |
fruitflies | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 7 | 3 |
furnace | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 3 |
girlht | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 70 | 3 |
glasses | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | table | 2 | 2 |
golf | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 105 | 14 |
gum | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 4 |
gunload | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 36 | 4 |
har1 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 2 |
har2 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 78 | 2 |
har3 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 30 | 2 |
hardness | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 36 | 2 |
heartvalve | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 4 |
hooppine | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 50 | 4 |
hospital | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 12 | 4 |
hotdog | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 54 | 3 |
houseprice | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 107 | 5 |
hpErie | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 28 | 12 |
htwt | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 39 | 7 |
iceskate | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 23 | 19 |
icu | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 200 | 21 |
income | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 51 | 3 |
inconsistent | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 210 | 2 |
intubate | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 20 | 4 |
ironpot | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 36 | 3 |
jury | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | array | | |
kangaroo | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 25 | 3 |
kidney | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 33 | 4 |
kyphosis | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 81 | 4 |
lake | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 20 | 2 |
leukemia | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 51 | 9 |
lft.asat | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 3938 | 4 |
lifeins | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 18 | 3 |
longley | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 16 | 7 |
lymph | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 53 | 7 |
maiz | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 40 | 4 |
manhours | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 25 | 8 |
market | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 48 | 4 |
mice | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 74 | 2 |
mileage | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 82 | 6 |
mortality | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | table | 2 | 2 |
mpg | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 50 | 3 |
muscle | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 16 | 2 |
njgolf | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 105 | 115 |
normtemp | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 130 | 3 |
notch | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 99 | 2 |
oats | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 72 | 7 |
odoffna | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 12 | 3 |
operator | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 20 | 2 |
oral | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | matrix | 2 | 2 |
ozone | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
paper | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 160 | 2 |
patient | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 64 | 2 |
plasma | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 50 | 3 |
political | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | table | 2 | 2 |
potency | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 15 | 2 |
pox | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 7 | 2 |
product | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
psycho | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 20 | 7 |
pulmonary | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 6 | 4 |
pulse | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 68 | 2 |
radioact | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 32 | 6 |
rent | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 67 | 6 |
retard | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 4 |
rhiz.alfalfa | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 60 | 5 |
rhiz.clover | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 60 | 5 |
rhizobium1 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 60 | 3 |
rhizobium3 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 60 | 3 |
salary | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 60 | 2 |
salinity | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 30 | 2 |
salk | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 4 |
seeding | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 26 | 2 |
selfexam | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | table | 3 | 3 |
shipment | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 20 | 3 |
sickle | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 41 | 2 |
skateslc | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 45 | 4 |
smokers | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 28 | 4 |
spacshu | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 138 | 2 |
spindle | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 3 |
sprint | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 23 | 2 |
stopdist | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 63 | 2 |
surface | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 3 |
tablet1 | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 2 |
teachers | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 32 | 2 |
testing | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 36 | 3 |
testscore | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 54 | 7 |
tires | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 16 | 4 |
tongue | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 24 | 2 |
tser.mystery.X | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
tser.mystery.Y | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
tser.mystery.Z | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
tsq | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | ts | | |
turkey | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 30 | 2 |
tv | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 40 | 5 |
usair | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 41 | 7 |
uscrime | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 47 | 15 |
vocab | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 54 | 1 |
vulcan | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 60 | 4 |
washday | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 21 | 2 |
water | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 61 | 3 |
weightloss | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 50 | 2 |
weld | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 36 | 5 |
wheat | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 20 | 6 |
wool | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 27 | 4 |
workstation | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 30 | 3 |
yates | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 72 | 7 |
yatesppl | HH | Datasets for Statistical Analysis and Data Display, Heiberger and Holland | data.frame | 72 | 9 |
FLOW_AMAX | LMoFit | Annual maximum flow data at Water Survey of Canada WSC flow gauge number 08NA002 in BC, Vancouver, Canada. Lat: 51ยฐ14'36.8ยจ N, Long: 116ยฐ54'46.6ยจ W. | numeric | | |
FLOW_AMAX_MULT | LMoFit | Annual maximum flow data at 10 hypothetical flow gauge. | data.frame | 112 | 10 |
lspace_BrIII | LMoFit | L-space of Burr Type-III Distribution (BrIII) | gg | | |
lspace_BrIII.xy | LMoFit | coordinates of the L-space of Burr Type-III Distribution (BrIII) | data.frame | 410 | 2 |
lspace_BrXII | LMoFit | L-space of Burr Type-XII Distribution (BrXII) | gg | | |
lspace_BrXII.xy | LMoFit | coordinates of the L-space of Burr Type-XII Distribution (BrXII) | data.frame | 239 | 2 |
lspace_GG | LMoFit | L-space of Generalized Gamma Distribution (GG) | gg | | |
lspace_GG.xy | LMoFit | coordinates of the L-space of Generalized Gamma Distribution (GG) | data.frame | 416 | 2 |
envData | MiRSEA | The variables in the environment include predefine pathway, target information of miRNAs,an expression profile and a example result of miRNA list | environment | | |
covid19.ontario | epigrowthfit | COVID-19 in Ontario, Canada | data.frame | 814 | 3 |
jackal | permute | Mandible lengths of male and female golden jackals | data.frame | 20 | 2 |
FANG | tibbletime | Stock prices for Facebook, Amazon, Netflix and Google from 2013-2016 | tbl_df | 4032 | 8 |
FB | tibbletime | Stock prices for Facebook from 2013-2016 | tbl_df | 1008 | 8 |
ALL_MORB__GALE__2013 | georefdatar | ALL_MORB | tbl_df | 1 | 70 |
Atmophile | georefdatar | Goldschmidt's classification of the elements | character | | |
BAB__GALE__2013 | georefdatar | BAB | tbl_df | 1 | 70 |
CC_Bulk__Rudnick_Gao__2014 | georefdatar | Bulk Continental Crust | tbl_df | 1 | 84 |
CC_Bulk__Taylor_McLennan__1995 | georefdatar | Bulk Continental Crust | tbl_df | 1 | 63 |
CC_Lower__Rudnick_Gao__2014 | georefdatar | Lower Continental Crust | tbl_df | 1 | 84 |
CC_Lower__Taylor_McLennan__1995 | georefdatar | Lower Continental Crust | tbl_df | 1 | 63 |
CC_Middle__Rudnick_Gao__2014 | georefdatar | Middle Continental Crust | tbl_df | 1 | 76 |
CC_Upper__Rudnick_Gao__2014 | georefdatar | Upper Continental Crust | tbl_df | 1 | 84 |
CC_Upper__Taylor_McLennan__1995 | georefdatar | Upper Continental Crust | tbl_df | 1 | 64 |
CI__McDonough_Sun__1995 | georefdatar | Chondrite | tbl_df | 1 | 76 |
Chalcophile | georefdatar | Goldschmidt's classification of the elements | character | | |
EMORB__Sun_McDounough__1989 | georefdatar | E-type MORB | tbl_df | 1 | 36 |
HREE | georefdatar | Rare earth elements - REE, LREE, MREE, HREE, REM, Lanthanides | character | | |
ICS_Colors | georefdatar | The CGMW ICS color codes | tbl_df | 194 | 11 |
IPGE | georefdatar | Platinum-group elements - PGE | character | | |
IUPAC_StdAW | georefdatar | IUPAC Standard atomic weights of the elements | data.frame | 118 | 8 |
LREE | georefdatar | Rare earth elements - REE, LREE, MREE, HREE, REM, Lanthanides | character | | |
Lanthanides | georefdatar | Rare earth elements - REE, LREE, MREE, HREE, REM, Lanthanides | character | | |
Lithophile | georefdatar | Goldschmidt's classification of the elements | character | | |
MREE | georefdatar | Rare earth elements - REE, LREE, MREE, HREE, REM, Lanthanides | character | | |
NMORB__Sun_McDounough__1989 | georefdatar | N-type MORB | tbl_df | 1 | 36 |
OIB__Sun_McDounough__1989 | georefdatar | Ocean Island Basalts - OIB | tbl_df | 1 | 36 |
PGE | georefdatar | Platinum-group elements - PGE | character | | |
PM__Sun_McDounough__1989 | georefdatar | Primitive mantle | tbl_df | 1 | 36 |
PPGE | georefdatar | Platinum-group elements - PGE | character | | |
Pyrolite__McDonough_Sun__1995 | georefdatar | Pyrolite | tbl_df | 1 | 76 |
REE | georefdatar | Rare earth elements - REE, LREE, MREE, HREE, REM, Lanthanides | character | | |
REM | georefdatar | Rare earth elements - REE, LREE, MREE, HREE, REM, Lanthanides | character | | |
Siderophile | georefdatar | Goldschmidt's classification of the elements | character | | |
decayConstants | georefdatar | Decay constants | data.frame | 6 | 5 |
isoRatios | georefdatar | Isotopic rations | data.frame | 3 | 4 |
mins | georefdatar | List of Minerals | tbl_df | 5744 | 4 |
pte | georefdatar | Periodic Table of Elements | data.frame | 118 | 17 |
hockey | BRcal | Hockey Home Team Win Predictions data | data.frame | 868 | 4 |
ann | RCSL | Cell type annotations of 'yan' datasets by Yan et al. | data.frame | 90 | 1 |
yan | RCSL | A public scRNA-seq dataset by Yan et al. | data.frame | 20214 | 90 |
Sim_data | probe | Simulated high-dimensional data set for sparse linear regression | list | | |
Sim_data_cov | probe | Simulated high-dimensional data set for sparse linear regression with non-sparse covariates. | list | | |
Sim_data_test | probe | Simulated high-dimensional test data set for sparse linear regression | list | | |
DCA | confidence | Annual Average 1,2-dichloroethane Concentration | data.frame | 3 | 10 |
EQR | confidence | Annual Average Environmental Quality Ratio for Macrofauna. | data.frame | 3 | 11 |
metal | confidence | Simulated Metal Contents | data.frame | 8 | 8 |
College | mvdalab | Data for College Level Examination Program and the College Qualification Test | data.frame | 87 | 3 |
Penta | mvdalab | Penta data set | data.frame | 30 | 17 |
Wang_Chen | mvdalab | Bivariate process data. | data.frame | 25 | 2 |
Wang_Chen_Sim | mvdalab | Simulated process data from a plastics manufacturer. | data.frame | 50 | 3 |
plusMinusDat | mvdalab | plusMinusDat data set | data.frame | 201 | 201 |
acceptor.m | SPLINTER | acceptor.m | matrix | 4 | 15 |
compatible_cds | SPLINTER | compatible_cds | list | | |
compatible_tx | SPLINTER | compatible_tx | list | | |
donor.m | SPLINTER | donor.m | matrix | 4 | 9 |
pcr_result1 | SPLINTER | pcr_result1 | data.frame | 1 | 2 |
primers | SPLINTER | primers | data.frame | 5 | 28 |
region_minus_exon | SPLINTER | region_minus_exon | CompressedGRangesList | | |
roi | SPLINTER | roi | list | | |
splice_data | SPLINTER | splice_data | list | | |
splice_fasta | SPLINTER | splice_fasta | data.frame | 5 | 2 |
thecds | SPLINTER | thecds | CompressedGRangesList | | |
theexons | SPLINTER | theexons | CompressedGRangesList | | |
valid_cds | SPLINTER | valid_cds | CompressedGRangesList | | |
valid_tx | SPLINTER | valid_tx | CompressedGRangesList | | |
BatchData | AMARETTO | BatchData | data.frame | 23263 | 3 |
Driver_Genes | AMARETTO | Driver_Genes | list | | |
MsigdbMapping | AMARETTO | MsigdbMapping | data.frame | 17810 | 3 |
ProcessedDataLIHC | AMARETTO | ProcessedDataLIHC | list | | |
sampleMiceDefs | miceRanger | Sample miceDefs object built off of iris dataset. Included so examples don't run for too long. | miceDefs | | |
kerenKontextual | Statial | Kontextual results from kerenSCE | data.frame | 4480 | 11 |
kerenSCE | Statial | MIBI-TOF Breast cancer intensities | SingleCellExperiment | | |
tictactoe | ReinforcementLearning | Game states of 100,000 randomly sampled Tic-Tac-Toe games. | data.frame | 406541 | 4 |
GRCh37 | CancerEvolutionVisualization | GRCh37 Chromosom Information | data.table | 24 | 3 |
GRCh38 | CancerEvolutionVisualization | GRCh38 Chromosom Information | data.table | 24 | 5 |
colours | CancerEvolutionVisualization | Colour scheme vector | character | | |
gd_es | geodimension | 'gd_es' | geodimension | | |
gd_us | geodimension | 'gd_us' | geodimension | | |
us_division | geodimension | 'us_division' | data.frame | 10 | 5 |
sce_chcl | scds | Example single cell experiment ('SingleCellExperiment') object | SingleCellExperiment | | |
zi_mo_hud | zippeR | Missouri HUD ZIP Code to County Crosswalk, 2023 | tbl_df | 1749 | 8 |
zi_mo_pop | zippeR | Total Population and Median Household Income, Missouri ZCTAs 2022 | tbl_df | 2664 | 4 |
zi_mo_usps | zippeR | Missouri USPS Three-digit ZIP Code Labels, August 2024 | tbl_df | 37 | 3 |
zi_mo_zcta3 | zippeR | Missouri Three-digit ZCTAs, 2022 | sf | 31 | 2 |
sysdata | autoBagging | sysdata | list | | |
gwasResults | qqman | Simulated GWAS results | data.frame | 16470 | 4 |
snpsOfInterest | qqman | snpsOfInterest | character | | |
DW | cem | Dehejia-Wahba dataset | data.frame | 445 | 12 |
LL | cem | Lalonde dataset | data.frame | 722 | 12 |
LLvsPSID | cem | Lalonde treated units versus PSID control individuals | data.frame | 2787 | 12 |
LeLonde | cem | Modified Lalonde dataset | data.frame | 722 | 13 |
ac | tidyCoverage | Example 'CoverageExperiment' and 'AggregatedCoverage' objects | AggregatedCoverage | | |
ce | tidyCoverage | Example 'CoverageExperiment' and 'AggregatedCoverage' objects | CoverageExperiment | | |
data_mouseMetabolism | AWFisher | Mouse metabolism microarray data | list | | |
followers | rgexf | Edge list with attributes | data.frame | 6064 | 6 |
twitteraccounts | rgexf | Twitter accounts of Chilean Politicians and Journalists (sample) | data.frame | 148 | 5 |
pos | falcon | Position (bp) | integer | | |
readMatrix | falcon | An example reads count data | data.frame | 6309 | 4 |
tauhat | falcon | Estimated Break Points | numeric | | |
AHFS_Codes_Drug | covid19dbcand | The American Hospital Formulary Service (AHFS) identifier for Drugs | spec_tbl_df | 15 | 2 |
ATC_Codes_Drug | covid19dbcand | Drug related ATC Codes | spec_tbl_df | 50 | 10 |
Actions_Carrier_Drug | covid19dbcand | Drug Carriers/ Enzymes/ Targets/ Transporters related Actions | spec_tbl_df | 15 | 2 |
Actions_Enzyme_Drug | covid19dbcand | Drug Carriers/ Enzymes/ Targets/ Transporters related Actions | spec_tbl_df | 90 | 2 |
Actions_Target_Drug | covid19dbcand | Drug Carriers/ Enzymes/ Targets/ Transporters related Actions | spec_tbl_df | 136 | 2 |
Actions_Transporter_Drug | covid19dbcand | Drug Carriers/ Enzymes/ Targets/ Transporters related Actions | spec_tbl_df | 55 | 2 |
Affected_Organisms_Drug | covid19dbcand | Drug related Affected Organisms | spec_tbl_df | 42 | 2 |
Articles_Carrier_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Articles | spec_tbl_df | 410 | 4 |
Articles_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Articles | spec_tbl_df | 238 | 4 |
Articles_Enzyme_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Articles | spec_tbl_df | 4003 | 4 |
Articles_Target_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Articles | spec_tbl_df | 1404 | 4 |
Articles_Transporter_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Articles | spec_tbl_df | 1312 | 4 |
Attachments | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters Attachments | spec_tbl_df | 3 | 4 |
Attachments_Carriers | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters Attachments | spec_tbl_df | 6 | 4 |
Attachments_Enzymes | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters Attachments | tbl_df | 388 | 4 |
Attachments_Targets | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters Attachments | spec_tbl_df | 11 | 4 |
Attachments_Transporters | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters Attachments | spec_tbl_df | 37 | 4 |
Books_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Books | spec_tbl_df | 1 | 4 |
Calculated_Properties_Drug | covid19dbcand | Drug Calculated Properties | spec_tbl_df | 596 | 4 |
Carriers_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | 15 | 6 |
Categories_Drug | covid19dbcand | Drug Categories General categorizations of the drug | spec_tbl_df | 633 | 3 |
Classifications_Drug | covid19dbcand | Drug Classification | spec_tbl_df | 20 | 9 |
Dosages_Drug | covid19dbcand | Drug Dosages A list of the commercially available dosages of the drug. | spec_tbl_df | 311 | 4 |
Drugs | covid19dbcand | Drugs | tbl_df | 33 | 15 |
Drugs_Pathway_Drug | covid19dbcand | Pathway Drugs Pathway Drugs Each drug may have one or more pathway and vise versa | spec_tbl_df | 33 | 3 |
Enzymes_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | 90 | 8 |
Enzymes_Pathway_Drug | covid19dbcand | Pathway Enzymes Enzymes involved in this pathway. | spec_tbl_df | 77 | 2 |
Enzymes_Reactions_Drug | covid19dbcand | Drug Reactions Enzymes Enzymes involved in metabolizing this drug. | spec_tbl_df | | 3 |
Experimental_Properties_Drug | covid19dbcand | Drug Experimental Properties | spec_tbl_df | 53 | 4 |
External_Identifiers_Drug | covid19dbcand | External Identifiers for Drugs/ Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | 232 | 3 |
External_Identifiers_Polypeptide_Carrier_Drug | covid19dbcand | External Identifiers for Drugs/ Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | | 3 |
External_Identifiers_Polypeptide_Enzyme_Drug | covid19dbcand | External Identifiers for Drugs/ Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | | 3 |
External_Identifiers_Polypeptide_Target_Drug | covid19dbcand | External Identifiers for Drugs/ Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | | 3 |
External_Identifiers_Transporter_Drug | covid19dbcand | External Identifiers for Drugs/ Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | | 3 |
External_Links_Drug | covid19dbcand | Drugs External Links. | spec_tbl_df | 26 | 3 |
Food_Interactions_Drug | covid19dbcand | Drug Food Interactions | spec_tbl_df | 19 | 2 |
GO_Classifiers_Polypeptide_Carrier_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters related Gene Ontology (GO) | spec_tbl_df | | 3 |
GO_Classifiers_Polypeptide_Target_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters related Gene Ontology (GO) | spec_tbl_df | | 3 |
GO_Classifiers_Polypeptide_Transporter_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters related Gene Ontology (GO) | spec_tbl_df | | 3 |
GO_Classifiers_Polypeptides_Enzyme_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters related Gene Ontology (GO) | spec_tbl_df | | 3 |
Groups_Drug | covid19dbcand | Drug Groups | spec_tbl_df | 43 | 2 |
Interactions_Drug | covid19dbcand | #' Drug Interactions | spec_tbl_df | 15476 | 4 |
International_Brands_Drug | covid19dbcand | Drug International Brands | spec_tbl_df | 130 | 3 |
Links_Carrier_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Links | spec_tbl_df | 88 | 4 |
Links_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Links | spec_tbl_df | 94 | 4 |
Links_Enzyme_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Links | tbl_df | 645 | 4 |
Links_Target_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Links | spec_tbl_df | 60 | 4 |
Links_Transporter_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Links | spec_tbl_df | 168 | 4 |
Manufacturers_Drug | covid19dbcand | Drug Manufacturers | spec_tbl_df | 46 | 4 |
Mixtures_Drug | covid19dbcand | Drug Mixture | spec_tbl_df | 819 | 3 |
PDB_Entries_Drug | covid19dbcand | Drug PDB Entries | spec_tbl_df | 120 | 2 |
PFAMS_Polypeptid_Transporter_Drug | covid19dbcand | PFAMs | spec_tbl_df | | 3 |
PFAMS_Polypeptide_Carrier_Drug | covid19dbcand | PFAMs | spec_tbl_df | | 3 |
PFAMS_Polypeptide_Target_Drug | covid19dbcand | PFAMs | spec_tbl_df | | 3 |
PFAMS_Polypeptides_Enzyme_Drug | covid19dbcand | PFAMs | spec_tbl_df | | 3 |
Packagers_Drug | covid19dbcand | Drug Packagers | spec_tbl_df | 370 | 3 |
Patents_Drug | covid19dbcand | Drug Patent | spec_tbl_df | 196 | 6 |
Pathways_Drug | covid19dbcand | Drug Pathways | spec_tbl_df | 4 | 4 |
Pharmacology | covid19dbcand | Drug Pharmacology | tbl_df | 33 | 12 |
Polypeptide_Target_Drug | covid19dbcand | Polypeptide | spec_tbl_df | 50 | 20 |
Polypeptides_Carrier_Drug | covid19dbcand | Polypeptide | spec_tbl_df | 3 | 20 |
Polypeptides_Enzyme_Drug | covid19dbcand | Polypeptide | spec_tbl_df | 35 | 20 |
Polypeptides_Transporter_Drug | covid19dbcand | Polypeptide | spec_tbl_df | 17 | 20 |
Prices_Drug | covid19dbcand | Drug Prices | spec_tbl_df | 208 | 5 |
Products_Drug | covid19dbcand | Drug Products | tbl_df | 3764 | 19 |
Reactions_Drug | covid19dbcand | Drug Reactions | spec_tbl_df | 69 | 6 |
SNP_Adverse_Drug_Reactions_Drug | covid19dbcand | SNP Adverse Drug Reactions | spec_tbl_df | | 9 |
SNP_Effects_Drug | covid19dbcand | Drug SNP Effects | spec_tbl_df | | 9 |
Salts_Drug | covid19dbcand | Drug Salts | spec_tbl_df | | 8 |
Sequences_Drug | covid19dbcand | Drug Sequences | spec_tbl_df | 4 | 3 |
Synonyms_Drug | covid19dbcand | Drugs Synonyms | spec_tbl_df | 105 | 4 |
Synonyms_Polypeptide_Carrier_Drug | covid19dbcand | Polypeptide Synonyms | spec_tbl_df | | 2 |
Synonyms_Polypeptide_Target_Drug | covid19dbcand | Polypeptide Synonyms | spec_tbl_df | | 2 |
Synonyms_Polypeptide_Transporter_Drug | covid19dbcand | Polypeptide Synonyms | spec_tbl_df | | 2 |
Synonyms_Polypeptides_Enzyme_Drug | covid19dbcand | Polypeptide Synonyms | spec_tbl_df | | 2 |
Targets_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | 59 | 6 |
Textbooks_Carrier_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Books | spec_tbl_df | 8 | 4 |
Textbooks_Enzyme_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Books | spec_tbl_df | 62 | 4 |
Textbooks_Target_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Books | spec_tbl_df | 11 | 4 |
Textbooks_Transporter_Drug | covid19dbcand | Drugs/ Carriers/ Enzymes/ Targets/ Transporters related Books | spec_tbl_df | 4 | 4 |
Transporters_Drug | covid19dbcand | Carriers/ Enzymes/ Targets/ Transporters | spec_tbl_df | 49 | 6 |
dark2 | campfin | Dark Color Palette | character | | |
extra_city | campfin | Additional US City Names | character | | |
invalid_city | campfin | Invalid City Names | character | | |
rx_phone | campfin | Phone number regex | character | | |
rx_state | campfin | State regex | glue | | |
rx_url | campfin | URL regex | character | | |
rx_zip | campfin | ZIP code regex | character | | |
usps_city | campfin | USPS City Abbreviations | tbl_df | 83 | 2 |
usps_state | campfin | USPS State Abbreviations | tbl_df | 62 | 2 |
usps_street | campfin | USPS Street Abbreviations | tbl_df | 368 | 2 |
valid_abb | campfin | US State Abbreviations | character | | |
valid_city | campfin | US City Names | character | | |
valid_name | campfin | US State Names | character | | |
valid_state | campfin | US State Abbreviations | character | | |
valid_zip | campfin | Almost all of the valid USA ZIP Codes | character | | |
zipcodes | campfin | US City, state, and ZIP | tbl_df | 44336 | 3 |
Agriculture | PSLM2015 | Agriculture data from Pakistan Social and Living Standard Measures 2015 | data.frame | 3324 | 97 |
Education | PSLM2015 | Education data from Pakistan Social and Living Standards Measurement 2015-16 | data.frame | 141828 | 22 |
Employment | PSLM2015 | Employment and income data from Pakistan Social and Living Standards Measurement 2015-16 | data.frame | 115910 | 27 |
Expenditure | PSLM2015 | Household's total expenditure data from Pakistan Social and Living Standards Measurement 2015-16 | data.frame | 24238 | 15 |
HHRoster | PSLM2015 | HouseHold roster data from Pakistan Social and Living Standards Measurement 2015-16 | data.frame | 157775 | 18 |
Housing | PSLM2015 | Housing data from Pakistan Social and Living Standards Measurement 2015-16 | data.frame | 24238 | 36 |
ICT | PSLM2015 | Information and communication technology data from Pakistan Social and Living Standard Measures 2015 | data.table | 115910 | 28 |
LiveStock | PSLM2015 | LiveStock data from Pakistan Social and Living Standard Measures 2015 | data.frame | 3771 | 116 |
housing | rineq | Artificial example data on housing conditions | data.table | 10000 | 10 |
cornsoybean | saeHB.unit | Corn and soy beans survey and satellite data in 12 counties in Iowa | data.frame | 37 | 5 |
cornsoybeanmeans | saeHB.unit | Corn and soy beans mean number of pixels per segment for 12 counties in Iowa. | data.frame | 12 | 6 |
dummy_area | saeHB.unit | dummy_area | data.table | 30 | 4 |
dummy_unit | saeHB.unit | dummy_unit | data.table | 1000 | 4 |
efsExample | oligoClasses | ExpressionFeatureSet Object | ExpressionFeatureSet | | |
locusLevelData | oligoClasses | Basic data elements required for the HMM | list | | |
oligoSet | oligoClasses | An example instance of oligoSnpSet class | oligoSnpSet | | |
scqsExample | oligoClasses | SnpCnvQSet Example | SnpCnvQSet | | |
sfsExample | oligoClasses | SnpFeatureSet Example | SnpFeatureSet | | |
sqsExample | oligoClasses | SnpQSet Example | SnpQSet | | |
data.activity.itempars | sirt | Item Parameters Cultural Activities | list | | |
data.befki | sirt | BEFKI Dataset (Schroeders, Schipolowski, & Wilhelm, 2015) | data.frame | 11756 | 12 |
data.befki_resp | sirt | BEFKI Dataset (Schroeders, Schipolowski, & Wilhelm, 2015) | matrix | 11756 | 12 |
data.big5 | sirt | Dataset Big 5 from 'qgraph' Package | matrix | 500 | 240 |
data.big5.qgraph | sirt | Dataset Big 5 from 'qgraph' Package | matrix | 500 | 240 |
data.bs07a | sirt | Datasets from Borg and Staufenbiel (2007) | data.frame | 100 | 9 |
data.eid | sirt | Examples with Datasets from Eid and Schmidt (2014) | numeric | | |
data.eid.kap4 | sirt | Examples with Datasets from Eid and Schmidt (2014) | data.frame | 193 | 11 |
data.eid.kap5 | sirt | Examples with Datasets from Eid and Schmidt (2014) | data.frame | 499 | 7 |
data.eid.kap6 | sirt | Examples with Datasets from Eid and Schmidt (2014) | data.frame | 238 | 7 |
data.eid.kap7 | sirt | Examples with Datasets from Eid and Schmidt (2014) | data.frame | 238 | 9 |
data.ess2005 | sirt | Dataset European Social Survey 2005 | list | | |
data.g308 | sirt | C-Test Datasets | data.frame | 747 | 20 |
data.inv4gr | sirt | Dataset for Invariance Testing with 4 Groups | data.frame | 4000 | 12 |
data.liking.science | sirt | Dataset 'Liking For Science' | matrix | 75 | 24 |
data.long | sirt | Longitudinal Dataset | data.frame | 200 | 13 |
data.lsem01 | sirt | Datasets for Local Structural Equation Models / Moderated Factor Analysis | data.frame | 989 | 6 |
data.lsem02 | sirt | Datasets for Local Structural Equation Models / Moderated Factor Analysis | data.frame | 1129 | 8 |
data.lsem03 | sirt | Datasets for Local Structural Equation Models / Moderated Factor Analysis | data.frame | 1027 | 10 |
data.math | sirt | Dataset Mathematics | list | | |
data.mcdonald.LSAT6 | sirt | Some Datasets from McDonald's _Test Theory_ Book | data.frame | 1004 | 5 |
data.mcdonald.act15 | sirt | Some Datasets from McDonald's _Test Theory_ Book | matrix | 15 | 15 |
data.mcdonald.rape | sirt | Some Datasets from McDonald's _Test Theory_ Book | list | | |
data.mixed1 | sirt | Dataset with Mixed Dichotomous and Polytomous Item Responses | data.frame | 1000 | 37 |
data.ml1 | sirt | Multilevel Datasets | data.frame | 2000 | 17 |
data.ml2 | sirt | Multilevel Datasets | data.frame | 2000 | 6 |
data.noharm18 | sirt | Datasets for NOHARM Analysis | data.frame | 200 | 18 |
data.noharmExC | sirt | Datasets for NOHARM Analysis | data.frame | 300 | 8 |
data.pars1.2pl | sirt | Item Parameters for Three Studies Obtained by 1PL and 2PL Estimation | data.frame | 22 | 4 |
data.pars1.rasch | sirt | Item Parameters for Three Studies Obtained by 1PL and 2PL Estimation | data.frame | 22 | 4 |
data.pirlsmissing | sirt | Dataset from PIRLS Study with Missing Responses | data.frame | 3480 | 38 |
data.pisaMath | sirt | Dataset PISA Mathematics | list | | |
data.pisaPars | sirt | Item Parameters from Two PISA Studies | data.frame | 25 | 4 |
data.pisaRead | sirt | Dataset PISA Reading | list | | |
data.pw01 | sirt | Datasets for Pairwise Comparisons | data.frame | 306 | 7 |
data.ratings1 | sirt | Rating Datasets | data.frame | 274 | 7 |
data.ratings2 | sirt | Rating Datasets | data.frame | 615 | 7 |
data.ratings3 | sirt | Rating Datasets | data.frame | 3169 | 6 |
data.raw1 | sirt | Dataset with Raw Item Responses | data.frame | 1200 | 77 |
data.read | sirt | Dataset Reading | data.frame | 328 | 12 |
data.reck21 | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.reck61DAT1 | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.reck61DAT2 | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.reck73C1a | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.reck73C1b | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.reck75C2 | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.reck78ExA | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.reck79ExB | sirt | Datasets from Reckase' Book _Multidimensional Item Response Theory_ | list | | |
data.si01 | sirt | Some Example Datasets for the 'sirt' Package | data.frame | 1857 | 3 |
data.si02 | sirt | Some Example Datasets for the 'sirt' Package | list | | |
data.si03 | sirt | Some Example Datasets for the 'sirt' Package | data.frame | 27 | 3 |
data.si04 | sirt | Some Example Datasets for the 'sirt' Package | list | | |
data.si05 | sirt | Some Example Datasets for the 'sirt' Package | list | | |
data.si06 | sirt | Some Example Datasets for the 'sirt' Package | data.frame | 4441 | 14 |
data.si07 | sirt | Some Example Datasets for the 'sirt' Package | list | | |
data.si08 | sirt | Some Example Datasets for the 'sirt' Package | data.frame | 32 | 6 |
data.si09 | sirt | Some Example Datasets for the 'sirt' Package | data.frame | 5201 | 13 |
data.si10 | sirt | Some Example Datasets for the 'sirt' Package | data.frame | 435 | 17 |
data.timss | sirt | Dataset TIMSS Mathematics | list | | |
data.timss07.G8.RUS | sirt | TIMSS 2007 Grade 8 Mathematics and Science Russia | list | | |
data.trees | sirt | Dataset Used in Stoyan, Pommerening and Wuensche (2018) | data.frame | 387 | 16 |
diseno1 | estadistica | Datos simulados de dos muestras tomadas en periodos de tiempo distintos. La muestra 1 es tomada en enero y la muestra 2 en junio. | data.frame | 610 | 2 |
diseno2 | estadistica | Datos simulados de dos muestras tomadas en periodos de tiempo distintos. La muestra 1 es tomada en enero y la muestra 2 en junio. | data.frame | 1085 | 2 |
ejem_bidi | estadistica | Data: Ejemplo de dos variables (ejem_bidi) | data.frame | 100 | 2 |
hogares | estadistica | Data: Hogares | data.frame | 10 | 3 |
salarios2018 | estadistica | Data: Encuesta cuatrienal de estructura salarial (2018) | data.frame | 216726 | 7 |
startup | estadistica | Data: Datos de empresas emergentes (startups) | data.frame | 21 | 4 |
turistas | estadistica | Data: Turistas por paises (WTO) | data.frame | 130 | 3 |
turistas2 | estadistica | Data: Turistas internacionales Comunidad Valenciana | data.frame | 80 | 2 |
viajes_vendidos | estadistica | Data: Viajes vendidos | data.frame | 5 | 3 |
Climat | multisensi | Climate data | data.frame | 3126 | 4 |
biomasseX | multisensi | A factorial input design for the main example | data.frame | 2187 | 7 |
biomasseY | multisensi | Output of the biomasse model for the plan provided in the package | data.frame | 2187 | 22 |
SVCdata | varycoef | Sampled SVC Data | list | | |
house | varycoef | Lucas County House Price Data | data.frame | 25357 | 25 |
ex_data | stpm | This is the longitudinal genetic dataset. | list | | |
earthquake_station | jmastats | Japan Meteorological Agency's earthquake observe stations | sf | 671 | 7 |
stations | jmastats | Japan Meteorological Agency's Stations list | sf | 1323 | 14 |
tide_station | jmastats | Tidal observation stations of Japan Meteorological Agency | sf | 1949 | 7 |
forstmann | EMC2 | Forstmann et al.'s data | data.frame | 15818 | 5 |
samples_LNR | EMC2 | An emc object of an LNR model of the Forstmann dataset using the first three subjects | emc | | |
Simulated_data | ATE.ERROR | Simulated Data | data.frame | 5000 | 6 |
cantius_L | paleoTS | Time-series of the length of lower first molar for the Cantius lineage | paleoTS | | |
dorsal.spines | paleoTS | Time-series of dorsal spine data from a fossil stickleback lineage | paleoTS | | |
CHOCOPhlAn_taxonomy | file2meco | The CHOCOPhlAn_taxonomy data | data.frame | 4984 | 6 |
MetaCyc_pathway_map | file2meco | The MetaCyc_pathway_map data | data.frame | 2720 | 3 |
ncyc_map | file2meco | The ncyc_map data | data.frame | 70 | 3 |
pcyc_map | file2meco | The pcyc_map data | data.frame | 140 | 4 |
Scenedesmus_apical | DRomics | Concentration-response effect of triclosan in Scenedesmus vacuolatus | data.frame | 3 | 37 |
Scenedesmus_metab | DRomics | Concentration-response effect of triclosan in Scenedesmus vacuolatus | data.frame | 225 | 25 |
Zhou_kidney_pce | DRomics | Dose-response kidney transcriptomic effect of Tetrachloroethylene in mouse | data.frame | 33395 | 15 |
zebraf | DRomics | Transcriptomic dose-response to ionizing radiation in zebrafish with batch effect | list | | |
msmdata | WeightIt | Simulated data for a 3 time point sequential study | data.frame | 7500 | 10 |
dummy_set | hmix | A simple data set with stock close prices | data.frame | 1925 | 4 |
bundData | NMOF | German Government Bond Data | list | | |
fundData | NMOF | Mutual Fund Returns | matrix | 500 | |
optionData | NMOF | Option Data | list | | |
FCV | abn | Dataset related to Feline calicivirus infection among cats in Switzerland. | data.frame | 300 | 15 |
adg | abn | Dataset related to average daily growth performance and abattoir findings in pigs commercial production. | data.frame | 341 | 9 |
ex0.dag.data | abn | Synthetic validation data set for use with abn library examples | data.frame | 300 | 30 |
ex1.dag.data | abn | Synthetic validation data set for use with abn library examples | data.frame | 10000 | 10 |
ex2.dag.data | abn | Synthetic validation data set for use with abn library examples | data.frame | 10000 | 18 |
ex3.dag.data | abn | Validation data set for use with abn library examples | data.frame | 1000 | 14 |
ex4.dag.data | abn | Valdiation data set for use with abn library examples | data.frame | 2000 | 11 |
ex5.dag.data | abn | Valdiation data set for use with abn library examples | data.frame | 434 | 19 |
ex6.dag.data | abn | Valdiation data set for use with abn library examples | data.frame | 800 | 8 |
ex7.dag.data | abn | Valdiation data set for use with abn library examples | data.frame | 10648 | 3 |
g2b2c_data | abn | Toy Data Set for Examples in README | data.frame | 1000 | 5 |
g2pbcgrp | abn | Toy Data Set for Examples in README | data.frame | 10000 | 6 |
pigs.vienna | abn | Dataset related to diseases present in 'finishing pigs', animals about to enter the human food chain at an abattoir. | data.frame | 25000 | 11 |
var33 | abn | simulated dataset from a DAG comprising of 33 variables | data.frame | 250 | 33 |
gmB | pcalg | Graphical Model 5-Dim Binary Example Data | list | | |
gmD | pcalg | Graphical Model Discrete 5-Dim Example Data | list | | |
gmG | pcalg | Graphical Model 8-Dimensional Gaussian Example Data | list | | |
gmG8 | pcalg | Graphical Model 8-Dimensional Gaussian Example Data | list | | |
gmI | pcalg | Graphical Model 7-dim IDA Data Examples | list | | |
gmI7 | pcalg | Graphical Model 7-dim IDA Data Examples | list | | |
gmInt | pcalg | Graphical Model 8-Dimensional Interventional Gaussian Example Data | list | | |
gmL | pcalg | Latent Variable 4-Dim Graphical Model Data Example | list | | |
barents | PLNmodels | Barents fish data set | data.frame | 89 | 6 |
mollusk | PLNmodels | Mollusk data set | list | | |
oaks | PLNmodels | Oaks amplicon data set | data.frame | 116 | 13 |
scRNA | PLNmodels | Single cell RNA-seq data | data.frame | 3918 | 3 |
trichoptera | PLNmodels | Trichoptera data set | list | | |
mip_example_data | mip | mip_example_data | magpie | | |
cultures_data | mpactr | LC-MS/MS sample data | filter_pactr | | |
hurricanes | DHARMa | Hurricanes | tbl_df | 92 | 14 |
fungusTreeNetwork | sbm | fungus-tree interaction network | list | | |
multipartiteEcologicalNetwork | sbm | Ecological multipartite interaction network | list | | |
war | sbm | War data set | list | | |
rhinos | rhino | Population of rhinos | tbl_df | 58 | 3 |
butterflies | untb | abundance data for butterflies | count | | |
caruso | untb | Dataset due to Caruso | matrix | 194 | 5 |
copepod | untb | Copepod data supplied by Phil Pugh | count | | |
ghats | untb | Tree counts in 1-ha plots from the Western Ghats mountains (South India) | data.frame | 304 | 50 |
ostracod | untb | Copepod data supplied by Phil Pugh | count | | |
sahfos | untb | Biodiversity dataset provided by SAHFOS | count | | |
saunders | untb | Dataset due to Saunders | data.frame | 40 | 177 |
saunders.tot | untb | Dataset due to Saunders | count | | |
spitale | untb | Counts of diatom species in springs of the Adamello-Brenta Nature Park | count | | |
esbl_tests | certestats | Example Data Set with ESBL Test Outcomes | tbl_df | 500 | 19 |
LondonYorke | pomp | Historical childhood disease incidence data | data.frame | 1968 | 7 |
blowflies | pomp | Nicholson's blowflies. | data.frame | 858 | 3 |
bsflu | pomp | Influenza outbreak in a boarding school | data.frame | 14 | 4 |
ebolaWA2014 | pomp | Ebola outbreak, West Africa, 2014-2016 | data.frame | 75 | 4 |
ewcitmeas | pomp | Historical childhood disease incidence data | data.frame | 14588 | 3 |
ewmeas | pomp | Historical childhood disease incidence data | data.frame | 991 | 2 |
parus | pomp | Parus major population dynamics | data.frame | 27 | 2 |
AssignDataAlien | IsoriX | Simulated assignment dataset | data.frame | 10 | 4 |
AssignDataBat | IsoriX | Assignment datasets for bat species | data.frame | 14 | 4 |
AssignDataBat2 | IsoriX | Assignment datasets for bat species | data.frame | 244 | 3 |
AssignDataBat2Rev | IsoriX | Assignment datasets for bat species | data.frame | 244 | 3 |
AssignDataBatRev | IsoriX | Assignment datasets for bat species | data.frame | 14 | 4 |
CalibDataAlien | IsoriX | Simulated calibration dataset | data.frame | 500 | 6 |
CalibDataBat | IsoriX | Calibration datasets for bat species | data.frame | 335 | 7 |
CalibDataBat2 | IsoriX | Calibration datasets for bat species | data.frame | 178 | 6 |
CalibDataBat2Rev | IsoriX | Calibration datasets for bat species | data.frame | 178 | 6 |
CalibDataBatRev | IsoriX | Calibration datasets for bat species | data.frame | 335 | 7 |
GNIPDataALLagg | IsoriX | Hydrogen delta values in precipitation water (aggregated per location) | data.frame | 921 | 7 |
GNIPDataDE | IsoriX | Hydrogen delta values in precipitation water, Germany | data.frame | 8591 | 7 |
GNIPDataEUagg | IsoriX | Hydrogen delta values in precipitation water (aggregated per location) | data.frame | 327 | 7 |
isopalette1 | IsoriX | Colour palettes for plotting | character | | |
isopalette2 | IsoriX | Colour palettes for plotting | character | | |
anscombe_tidy | cassowaryr | Data from Anscombe's famous example in tidy format | tbl_df | 44 | 3 |
datasaurus_dozen | cassowaryr | datasaurus_dozen data | tbl_df | 1846 | 3 |
datasaurus_dozen_wide | cassowaryr | datasaurus_dozen data | tbl_df | 142 | 26 |
features | cassowaryr | Simulated data with special features | tbl_df | 1913 | 3 |
numbat | cassowaryr | A toy data set with a numbat shape hidden among noise variables | tbl_df | 2100 | 10 |
pk | cassowaryr | Parkinsons data from UCI machine learning archive | spec_tbl_df | 195 | 24 |
Demo.growth | lavaan | Demo dataset for a illustrating a linear growth model. | data.frame | 400 | 10 |
Demo.twolevel | lavaan | Demo dataset for a illustrating a multilevel CFA. | data.frame | 2500 | 12 |
FacialBurns | lavaan | Dataset for illustrating the InformativeTesting function. | data.frame | 77 | 6 |
HolzingerSwineford1939 | lavaan | Holzinger and Swineford Dataset (9 Variables) | data.frame | 301 | 15 |
PoliticalDemocracy | lavaan | Industrialization And Political Democracy Dataset | data.frame | 75 | 11 |
candies | multiblock | Sensory assessment of candies. | data.frame | 165 | 3 |
potato | multiblock | Sensory, rheological, chemical and spectroscopic analysis of potatoes. | data.frame | 26 | 9 |
simulated | multiblock | Data simulated to have certain characteristics. | list | | |
wine | multiblock | Wines of Val de Loire | data.frame | 21 | 5 |
efc | datawizard | Sample dataset from the EFC Survey | data.frame | 100 | 5 |
nhanes_sample | datawizard | Sample dataset from the National Health and Nutrition Examination Survey | tbl_df | 2992 | 7 |
Fischbein_wt | umx | Weight data across time. | data.frame | 6 | 6 |
GFF | umx | Twin data: General Family Functioning, divorce, and well-being. | data.frame | 3185 | 47 |
docData | umx | Twin data for Direction of causation modelling | data.frame | 1400 | 13 |
iqdat | umx | Twin data: IQ measured longitudinally across 4 ages. | data.frame | 562 | 9 |
us_skinfold_data | umx | Anthropometric data on twins | data.frame | 395 | 20 |
defaultPrescriptionsBySpecies | medfateland | Default prescriptions by species | data.frame | 27 | 20 |
example_ifn | medfateland | Example of distributed forest inventory stands | sf | 100 | 8 |
example_watershed | medfateland | Example of watershed | sf | 66 | 15 |
example_watershed_burnin | medfateland | Example of watershed | sf | 66 | 15 |
signals | gsignal | signals | data.frame | 2560 | 2 |
cran_monthly_package_number | cranology | cran_monthly_package_number | tbl_df | 324 | 2 |
cran_packages_history | cranology | cran_packages_history | tbl_df | 44613 | 10 |
iran.quakes | ETAS | An Iranian Earthquake Catalog | data.frame | 5970 | 5 |
italy.quakes | ETAS | An Italian Earthquake Catalog | data.frame | 2158 | 6 |
japan.quakes | ETAS | A Japanese Earthquake Catalog | data.frame | 13724 | 6 |
harmonization_lookup_tables | iidda | Harmonization Lookup Tables | list | | |
standards | iidda | Standards | list | | |
Laurasiatherian | phangorn | Laurasiatherian data (AWCMEE) | phyDat | | |
chloroplast | phangorn | Chloroplast alignment | phyDat | | |
mites | phangorn | Morphological characters of Mites (Schรคffer et al. 2010) | phyDat | | |
yeast | phangorn | Yeast alignment (Rokas et al.) | phyDat | | |
Melanoma | riskRegression | Malignant melanoma data | data.frame | 205 | 11 |
Paquid | riskRegression | Paquid sample | data.frame | 2561 | 4 |
abcd_demo | r2dii.data | An asset-based company dataset for demonstration | tbl_df | 4972 | 12 |
co2_intensity_scenario_demo | r2dii.data | A prepared co2 intensity climate scenario dataset for demonstration | tbl_df | 22 | 7 |
data_dictionary | r2dii.data | Column definitions of all datasets | tbl_df | 96 | 4 |
gics_classification | r2dii.data | Dataset to bridge (translate) common sector-classification codes | tbl_df | 282 | 5 |
increasing_or_decreasing | r2dii.data | Determine if a technology is increasing or decreasing | tbl_df | 20 | 3 |
isic_classification | r2dii.data | Dataset to bridge (translate) common sector-classification codes | tbl_df | 830 | 6 |
iso_codes | r2dii.data | Countries and codes | tbl_df | 286 | 2 |
loanbook_demo | r2dii.data | A loanbook dataset for demonstration | tbl_df | 283 | 13 |
nace_classification | r2dii.data | Dataset to bridge (translate) common sector-classification codes | tbl_df | 1047 | 6 |
naics_classification | r2dii.data | Dataset to bridge (translate) common sector-classification codes | tbl_df | 2125 | 5 |
overwrite_demo | r2dii.data | A demonstration dataset used to overwrite specific entity names or sectors | tbl_df | 2 | 5 |
psic_classification | r2dii.data | Dataset to bridge (translate) common sector-classification codes | tbl_df | 1271 | 5 |
region_isos | r2dii.data | A dataset outlining various region definitions | tbl_df | 9262 | 3 |
region_isos_demo | r2dii.data | A dataset outlining various region definitions | tbl_df | 358 | 3 |
scenario_demo_2020 | r2dii.data | A prepared climate scenario dataset for demonstration | tbl_df | 1512 | 8 |
sector_classifications | r2dii.data | A view of available sector classification datasets | tbl_df | 6559 | 4 |
sic_classification | r2dii.data | Dataset to bridge (translate) common sector-classification codes | tbl_df | 1005 | 5 |
closure_data | daedalus | Pandemic response strategy data for DAEDALUS | list | | |
country_data | daedalus | Country demographic data for DAEDALUS | list | | |
country_names | daedalus | Country names for DAEDALUS | character | | |
economic_contacts | daedalus | Economic sector contacts data for DAEDALUS | list | | |
epidemic_names | daedalus | Infection characteristics for model epidemics | character | | |
infection_data | daedalus | Infection characteristics for model epidemics | list | | |
infection_parameter_names | daedalus | Infection characteristics for model epidemics | character | | |
dube | DiSCos | Data from (Dube 2019) | data.table | 652870 | 3 |
creditCard | StepReg | creditCard | data.frame | 1319 | 12 |
remission | StepReg | remission | data.frame | 27 | 7 |
tobacco | StepReg | tobacco | data.frame | 25 | 9 |
alignment_scores_values | pacta.executive.summary | Help dataset for plotting alignment scores on an axis | tbl_df | 6 | 5 |
p4i_p4b_sector_technology_mapper | pacta.executive.summary | Sector and technology names mapped from P4I to P4B style | tbl_df | 28 | 4 |
remaining_carbon_budgets | pacta.executive.summary | Sector level carbon budgets for scenarios | tbl_df | 8 | 5 |
scenario_thresholds | pacta.executive.summary | Scenario names mapped to temperature thresholds | tbl_df | 9 | 3 |
scores_real_estate | pacta.executive.summary | Help dataset for plotting real estate scores | tbl_df | 7 | 5 |
toy_data_alignment_table | pacta.executive.summary | An example output data of 'prep_alignment_table()' | tbl_df | 40 | 7 |
toy_data_diagram | pacta.executive.summary | An example output data of 'prep_diagram()' | tbl_df | 2 | 8 |
toy_data_emissions_scorecard | pacta.executive.summary | An example output data of 'prep_emissions_scorecard()' | tbl_df | 4 | 3 |
toy_data_exposures_scorecard | pacta.executive.summary | An example output data of 'prep_exposures_scorecard()' | tbl_df | 8 | 3 |
toy_data_exposures_survey | pacta.executive.summary | An example output data of 'prep_exposures_survey()' | tbl_df | 12 | 4 |
toy_data_fossil_bars | pacta.executive.summary | An example output data of 'prep_fossil_bars()' | tbl_df | 18 | 7 |
toy_data_green_brown_bars | pacta.executive.summary | An example output data of 'prep_green_brown_bars()' | tbl_df | 18 | 6 |
toy_data_scatter | pacta.executive.summary | An example output data of 'prep_scatter()' | tbl_df | 14 | 6 |
toy_data_scores | pacta.executive.summary | An example output data of 'prep_scores()' | tbl_df | 28 | 5 |
toy_data_scores_scorecard_re | pacta.executive.summary | An example input data to 'plot_scores_scorecard_real_estate()' | tbl_df | 2 | 2 |
data_dictionary | workflow.multi.loanbook | Data dictionary | tbl_df | 220 | 5 |
asdgap | rchemo | asdgap | list | | |
cassav | rchemo | cassav | list | | |
forages | rchemo | forages | list | | |
octane | rchemo | octane | list | | |
ozone | rchemo | ozone | list | | |
Cliff_walking | markovDP | Cliff Walking Gridworld MDP | MDP | | |
DynaMaze | markovDP | The Dyna Maze | MDP | | |
Maze | markovDP | Steward Russell's 4x3 Maze Gridworld MDP | MDP | | |
Windy_gridworld | markovDP | Windy Gridworld MDP Windy Gridworld MDP | MDP | | |
CarboCATLite_data | admtools | Example data from CarboCATLite | list | | |
timetree | admtools | example time tree | phylo | | |
osm_amenities | nominatimlite | OpenStreetMap amenity database | tbl_df | 136 | 3 |
gasoline | pls | Octane numbers and NIR spectra of gasoline | data.frame | 60 | 2 |
mayonnaise | pls | NIR measurements and oil types of mayonnaise | data.frame | 162 | 4 |
oliveoil | pls | Sensory and physico-chemical data of olive oils | data.frame | 16 | 2 |
yarn | pls | NIR spectra and density measurements of PET yarns | data.frame | 28 | 3 |
isotopes | IsoCor | isotopes. | data.frame | 308 | 5 |
testdata | IsoCor | testdata. | list | | |
testdata_IDMS | IsoCor | testdata_IDMS. | list | | |
dailyrainfall | mevr | Daily rainfall data | data.frame | 2688 | 2 |
shipley | semEff | Simulated Data from Shipley (2009) | data.frame | 1900 | 9 |
shipley.growth | semEff | Candidate Model Set from Shipley 'Growth' Model | list | | |
shipley.sem | semEff | Hypothesised SEM from Shipley (2009) | list | | |
shipley.sem.boot | semEff | Bootstrapped Estimates for Shipley SEM | list | | |
shipley.sem.eff | semEff | Effects for Shipley SEM | semEff | | |
polymod | socialmixr | Social contact data from 8 European countries | survey | | |
Bilagay | tRophicPosition | Data frame containing stable isotope values of Bilagay. | data.frame | 841 | 7 |
Finnish_Lakes | tRophicPosition | Data frame of food webs in Inari and Kilpis Lakes (Finland) | data.frame | 1258 | 7 |
Orestias | tRophicPosition | Named list containing stable isotope values of Orestias chungarensis | list | | |
Roach | tRophicPosition | Data frame of Roach in Lough Neagh | data.frame | 181 | 6 |
Trout | tRophicPosition | Named list containing stable isotope values of Oncorhynchus mykiss | list | | |
available_price_indexes | realtalk | Price indexes available in the 'realtalk' package | tbl_df | 20 | 6 |
c_cpi_u_annual | realtalk | Chained Consumer Price Index for Urban Consumers (C-CPI-U) data | tbl_df | 24 | 2 |
c_cpi_u_extended_annual | realtalk | Extended Chained Consumer Price Index for Urban Consumers (C-CPI-U) | tbl_df | 87 | 2 |
c_cpi_u_extended_monthly_nsa | realtalk | Extended Chained Consumer Price Index for Urban Consumers (C-CPI-U) | tbl_df | 1052 | 3 |
c_cpi_u_extended_monthly_sa | realtalk | Extended Chained Consumer Price Index for Urban Consumers (C-CPI-U) | tbl_df | 932 | 3 |
c_cpi_u_extended_quarterly_nsa | realtalk | Extended Chained Consumer Price Index for Urban Consumers (C-CPI-U) | tbl_df | 350 | 3 |
c_cpi_u_extended_quarterly_sa | realtalk | Extended Chained Consumer Price Index for Urban Consumers (C-CPI-U) | tbl_df | 310 | 3 |
c_cpi_u_monthly_nsa | realtalk | Chained Consumer Price Index for Urban Consumers (C-CPI-U) data | tbl_df | 297 | 3 |
c_cpi_u_quarterly_nsa | realtalk | Chained Consumer Price Index for Urban Consumers (C-CPI-U) data | tbl_df | 98 | 3 |
cpi_u_annual | realtalk | Consumer Price Index for Urban Consumers (CPI-U) data | tbl_df | 87 | 2 |
cpi_u_monthly_nsa | realtalk | Consumer Price Index for Urban Consumers (CPI-U) data | tbl_df | 1052 | 3 |
cpi_u_monthly_sa | realtalk | Consumer Price Index for Urban Consumers (CPI-U) data | tbl_df | 932 | 3 |
cpi_u_quarterly_nsa | realtalk | Consumer Price Index for Urban Consumers (CPI-U) data | tbl_df | 350 | 3 |
cpi_u_quarterly_sa | realtalk | Consumer Price Index for Urban Consumers (CPI-U) data | tbl_df | 310 | 3 |
cpi_u_rs_annual | realtalk | Consumer Price Index for Urban Consumers Research Series (CPI-U-RS) data | tbl_df | 46 | 2 |
cpi_u_rs_monthly_nsa | realtalk | Consumer Price Index for Urban Consumers Research Series (CPI-U-RS) data | tbl_df | 553 | 3 |
cpi_u_x1_annual | realtalk | Experimental Consumer Price Index for Urban Consumers X1 (CPI-U-X1) data | tbl_df | 16 | 2 |
cpi_u_x1_monthly_nsa | realtalk | Experimental Consumer Price Index for Urban Consumers X1 (CPI-U-X1) data | tbl_df | 192 | 3 |
pce_annual | realtalk | Personal Consumption Expenditures (PCE) price index | tbl_df | 95 | 2 |
pce_monthly_sa | realtalk | Personal Consumption Expenditures (PCE) price index | tbl_df | 787 | 3 |
pce_quarterly_sa | realtalk | Personal Consumption Expenditures (PCE) price index | tbl_df | 310 | 3 |
us_minimum_wage_annual | realtalk | Example nominal US federal minimum wage data | tbl_df | 87 | 2 |
us_minimum_wage_monthly | realtalk | Example nominal US federal minimum wage data | tbl_df | 1035 | 3 |
MetroFull | skynet | Metro (Full) Data | data.frame | 5802 | 6 |
MetroLookup | skynet | Metro Data | tbl_df | 5782 | 4 |
OD_Sample | skynet | Sample OD data | data.frame | 4000 | 19 |
aircraft_type | skynet | Aircraft type data | spec_tbl_df | 422 | 2 |
airportCode | skynet | Airport Data - clean | data.table | 6435 | 5 |
airportCodeFull | skynet | Airport Data - full | data.table | 6435 | 9 |
airportMaster | skynet | Airport Data - master | data.table | 13555 | 28 |
carriers | skynet | Carrier data | data.table | 1882 | 5 |
NTDs | gdverse | NTDs data | tbl_df | 185 | 6 |
ndvi | gdverse | dataset of NDVI changes and its influencing factors | tbl_df | 713 | 7 |
sim | gdverse | Simulation data. | tbl_df | 80 | 6 |
srs_table | gdverse | example of spatial information system table | tbl_df | 11 | 5 |
srs_wt | gdverse | example of spatial information system spatial adjacency matrix | matrix | 11 | |
articulations | tabr | Single note articulations and syntax | data.frame | 44 | 3 |
guitarChords | tabr | Predefined guitar chords | tbl_df | 3967 | 12 |
mainIntervals | tabr | Main musical intervals | data.frame | 26 | 5 |
tabrSyntax | tabr | tabr syntax | data.frame | 15 | 3 |
tunings | tabr | Predefined instrument tunings | data.frame | 32 | 2 |
obs_temp | dycdtools | Example observed profiling temperature data across different depths over the period of 6-11 June 2017. | data.frame | 77 | 3 |
output_name | dycdtools | Default DYCD simulation variable names with their variable name | data.frame | 65 | 2 |
CHOL.DEGs | easybio | Example DEGs data from Limma-Voom workflow for TCGA-CHOL project | data.frame | 21938 | 21 |
pbmc.markers | easybio | Example marker data from Seurat::FindAllMarkers() | data.frame | 11629 | 7 |
class_to_col_type | ohcleandat | Class to Column Type lookup table | data.frame | 9 | 3 |
game_revenue | pointblank | A table with game revenue data | tbl_df | 2000 | 11 |
game_revenue_info | pointblank | A table with metadata for the 'game_revenue' dataset | tbl_df | 11 | 2 |
small_table | pointblank | A small table that is useful for testing | spec_tbl_df | 13 | 8 |
specifications | pointblank | A table containing data pertaining to various specifications | tbl_df | 8 | 12 |
E_nc1 | inlabru | 1-Dimensional Homogeneous Poisson example. | numeric | | |
E_nc2 | inlabru | 1-Dimensional NonHomogeneous Poisson example. | numeric | | |
E_nc3a | inlabru | 1-Dimensional NonHomogeneous Poisson example. | numeric | | |
E_nc3b | inlabru | 1-Dimensional NonHomogeneous Poisson example. | numeric | | |
countdata1 | inlabru | 1-Dimensional Homogeneous Poisson example. | data.frame | 11 | 3 |
countdata2 | inlabru | 1-Dimensional NonHomogeneous Poisson example. | data.frame | 11 | 3 |
countdata3a | inlabru | 1-Dimensional NonHomogeneous Poisson example. | data.frame | 10 | 3 |
countdata3b | inlabru | 1-Dimensional NonHomogeneous Poisson example. | data.frame | 20 | 3 |
cov2_1D | inlabru | 1-Dimensional NonHomogeneous Poisson example. | function | | |
gorillas | inlabru | Gorilla nesting sites | list | | |
gorillas_sf | inlabru | Gorilla nesting sites in sf format | list | | |
lambda1_1D | inlabru | 1-Dimensional Homogeneous Poisson example. | function | | |
lambda2_1D | inlabru | 1-Dimensional NonHomogeneous Poisson example. | function | | |
lambda3_1D | inlabru | 1-Dimensional NonHomogeneous Poisson example. | function | | |
mexdolphin | inlabru | Pan-tropical spotted dolphins in the Gulf of Mexico | list | | |
mexdolphin_sf | inlabru | Pan-tropical spotted dolphins in the Gulf of Mexico | list | | |
mrsea | inlabru | Marine renewables strategic environmental assessment | list | | |
pts1 | inlabru | 1-Dimensional Homogeneous Poisson example. | data.frame | 116 | 1 |
pts2 | inlabru | 1-Dimensional NonHomogeneous Poisson example. | data.frame | 130 | 1 |
pts3 | inlabru | 1-Dimensional NonHomogeneous Poisson example. | data.frame | 408 | 1 |
robins_subset | inlabru | robins_subset | data.frame | 5807 | 10 |
seals_sp | inlabru | Seal pups | list | | |
shrimp | inlabru | Blue and red shrimp in the Western Mediterranean Sea | list | | |
toygroups | inlabru | Simulated 1D animal group locations and group sizes | list | | |
toypoints | inlabru | Simulated 2D point process data | list | | |
legoCols | legocolors | Lego color data. | tbl_df | 167 | 12 |
legoPals | legocolors | Lego color palettes. | list | | |
metadata_forestdata | forestdata | Metadata for 'forestdata' functions | list | | |
AgroClimateData | AquaBEHER | Daily Surface Meteorological Data (1982-2022) Extracted from AgERA5 | data.frame | 14975 | 14 |
climateData | AquaBEHER | Daily Weather Data (1996-2020) from Angochen Weather Observing Station, Mozambique | data.frame | 9132 | 10 |
coffee_data | ggeffects | Sample dataset from a course about analysis of factorial designs | data.frame | 120 | 5 |
efc | ggeffects | Sample dataset from the EUROFAMCARE project | data.frame | 908 | 28 |
efc_test | ggeffects | Sample dataset from the EUROFAMCARE project | data.frame | 908 | 28 |
fish | ggeffects | Sample data set | data.frame | 250 | 9 |
lung2 | ggeffects | Sample data set | data.frame | 226 | 5 |
BriggsEx47 | rdecision | Probabilistic results of HIV model | data.frame | 1000 | 7 |
mirESCA | plasma | ESCA type data | data.frame | 195 | 2 |
tfESCA | plasma | ESCA type data | data.frame | 196 | 2 |
bbsData | spAbundance | Count data for six warbler species in Pennsylvania, USA | list | | |
bbsPredData | spAbundance | Covariates and coordinates for prediction of relative warbler abundance in Pennsylvania, USA | data.frame | 816 | 7 |
dataNMixSim | spAbundance | Simulated repeated count data of 6 species across 225 sites | list | | |
hbefCount2015 | spAbundance | Count data of 12 foliage gleaning bird species in 2015 in the Hubbard Brook Experimental Forest | list | | |
neonDWP | spAbundance | Distance sampling data of 16 bird species observed in the Disney Wilderness Preserve in 2018 in Florida, USA | list | | |
neonPredData | spAbundance | Land cover covariates and coordinates at a 1ha resolution across Disney Wilderness Preserve | data.frame | 4838 | 4 |
Dark24 | Polychrome | Light and Dark 24-Color Palettes | character | | |
Light24 | Polychrome | Light and Dark 24-Color Palettes | character | | |
alphabet | Polychrome | A 26-Color Palette | character | | |
colorsafe | Polychrome | A 10-Color Palette Distinguishable By COlor-Deficit Individuals | character | | |
glasbey | Polychrome | The 32-color Glasbye palette | character | | |
iscc | Polychrome | Color Names From the Inter-Society Color Council (ISCC) | data.frame | 267 | 3 |
palette36 | Polychrome | A 36-Color Palette | character | | |
sky.colors | Polychrome | Polychrome Color Palettes | character | | |
spiders | cotram | Bavarian Forest Spider Data | data.frame | 190 | 9 |
clinical.info | oompaData | Experimental info for the prostate cancer data set | data.frame | 112 | 6 |
expression.data | oompaData | Microarray expression data on prostate cancer | data.frame | 2000 | 112 |
gene.info | oompaData | Gene information for the prostate cancer data set | data.frame | 2000 | 6 |
lung.clinical | oompaData | Lung Cancer Gene Expression Dataset | data.frame | 444 | 10 |
lung.dataset | oompaData | Lung Cancer Gene Expression Dataset | matrix | 150 | 444 |
example | momentuHMM | Example dataset | list | | |
forest | momentuHMM | Example dataset | RasterLayer | | |
miExample | momentuHMM | Example dataset | list | | |
tasky | ssrhom | Dataset from Tasky et al. (2008) | data.frame | 70 | 5 |
January_PDO | rshift | Pacific Decadal Oscillation in January | data.frame | 104 | 2 |
lake_RSI | rshift | DCA-ordinated pollen data from Lake Consuelo with RSI values | spec_tbl_df | 39 | 3 |
lake_data | rshift | DCA-ordinated pollen data from Lake Consuelo | spec_tbl_df | 39 | 2 |
alarm | bnlearn | ALARM monitoring system (synthetic) data set | data.frame | 20000 | 37 |
asia | bnlearn | Asia (synthetic) data set by Lauritzen and Spiegelhalter | data.frame | 5000 | 8 |
clgaussian.test | bnlearn | Synthetic (mixed) data set to test learning algorithms | data.frame | 5000 | 8 |
coronary | bnlearn | Coronary heart disease data set | data.frame | 1841 | 6 |
gaussian.test | bnlearn | Synthetic (continuous) data set to test learning algorithms | data.frame | 5000 | 7 |
hailfinder | bnlearn | The HailFinder weather forecast system (synthetic) data set | data.frame | 20000 | 56 |
insurance | bnlearn | Insurance evaluation network (synthetic) data set | data.frame | 20000 | 27 |
learning.test | bnlearn | Synthetic (discrete) data set to test learning algorithms | data.frame | 5000 | 6 |
lizards | bnlearn | Lizards' perching behaviour data set | data.frame | 409 | 3 |
marks | bnlearn | Examination marks data set | data.frame | 88 | 5 |
ecpe_data | measr | Examination for the Certificate of Proficiency in English (ECPE) | spec_tbl_df | 2922 | 29 |
ecpe_qmatrix | measr | Examination for the Certificate of Proficiency in English (ECPE) | tbl_df | 28 | 4 |
mdm_data | measr | MacReady & Dayton (1977) Multiplication Data | tbl_df | 142 | 5 |
mdm_qmatrix | measr | MacReady & Dayton (1977) Multiplication Data | tbl_df | 4 | 2 |
bcva_data | mmrm | Example Data on BCVA | data.frame | 8605 | 7 |
cached_mmrm_results | mmrm | Cache Data for 'mmrm' Model Comparison | list | | |
fev_data | mmrm | Example Data on FEV1 | data.frame | 800 | 10 |
sim_area | apcf | Simulated Patterns (sample data) | wk_wkb | | |
sim_pat_clust | apcf | Simulated Patterns (sample data) | wk_wkb | | |
sim_pat_rand | apcf | Simulated Patterns (sample data) | wk_wkb | | |
sim_pat_reg | apcf | Simulated Patterns (sample data) | wk_wkb | | |
dat | ktweedie | A demo dataset | list | | |
rats | TSHRC | Litter-matched Time-to-response Data | data.frame | 150 | 3 |
dgrp2.3R.5k.data | GenomeAdmixR | A subset of sequencing data from the Drosophila Genetics Reference Panel | genomeadmixr_data | | |
CNAchrom11 | Rbeast | DNA copy number alteration data in array-based CGH data for Chromesome 11 | numeric | | |
Yellowstone | Rbeast | 30 years' AVHRR NDVI data at a Yellostone site | numeric | | |
covid19 | Rbeast | Daily confirmed COVID19 cases and deaths in the world | data.frame | 1037 | 4 |
googletrend_beach | Rbeast | A monthly Google Trend time series of the US search interest in the word "beach" | ts | | |
imagestack | Rbeast | Decades of Landsat NDVI time series over a small area in Ohio | list | | |
ohio | Rbeast | An irregular Landsat NDVI time series at an Ohio site | data.frame | 400 | 17 |
simdata | Rbeast | Simulated time series to test BEAST | matrix | 300 | |
Anduki | tigers | Anduki Forest Reserve | matrix | 61 | |
datapack_psnu_area_level | threemc | PSNU Area Levels for SSA | data.table | 29 | 2 |
demo_areas | threemc | Malawi shapefiles | sf | 532 | 10 |
demo_populations | threemc | Malawi populations | tbl_df | 176418 | 7 |
demo_survey_circumcision | threemc | Malawi surveys | tbl_df | 29153 | 13 |
esa_wca_regions | threemc | WCA - ESA key for Sub-Saharan African countries | spec_tbl_df | 38 | 3 |
example_confirmed | EpiNow2 | Example Confirmed Case Data Set | data.table | 130 | 2 |
example_generation_time | EpiNow2 | Example generation time | dist_spec | | |
example_incubation_period | EpiNow2 | Example incubation period | dist_spec | | |
example_reporting_delay | EpiNow2 | Example reporting delay | dist_spec | | |
example_truncated | EpiNow2 | Example Case Data Set with Truncation | list | | |
generation_times | EpiNow2 | Literature Estimates of Generation Times | data.table | 1 | 9 |
incubation_periods | EpiNow2 | Literature Estimates of Incubation Periods | data.table | 1 | 9 |
mimeTypeExtensions | RCurl | Mapping from extension to MIME type | character | | |
brain | DRIP | Brain Image | matrix | 217 | |
circles | DRIP | Image of Circles | matrix | 256 | |
kid | DRIP | Image of a Kid | matrix | 387 | |
lena | DRIP | Lena Image | matrix | 512 | |
peppers | DRIP | Image of Peppers | matrix | 512 | |
sar | DRIP | Synthetic Aperture Radar Image | matrix | 250 | |
stopsign | DRIP | Stop Sign Image | matrix | 160 | |
sim_boundary_data | prioriactions | Simulated multi-action planning data | data.frame | 10000 | 3 |
sim_dist_features_data | prioriactions | Simulated multi-action planning data | data.frame | 176 | 3 |
sim_dist_threats_data | prioriactions | Simulated multi-action planning data | data.frame | 120 | 5 |
sim_features_data | prioriactions | Simulated multi-action planning data | data.frame | 4 | 3 |
sim_pu_data | prioriactions | Simulated multi-action planning data | data.frame | 100 | 3 |
sim_sensitivity_data | prioriactions | Simulated multi-action planning data | data.frame | 8 | 2 |
sim_threats_data | prioriactions | Simulated multi-action planning data | data.frame | 2 | 3 |
usmacro_growth | bayesianVARs | Data from the US-economy | matrix | 247 | 21 |
acupuncture | RefBasedMI | Sample data: acupuncture trial | data.frame | 802 | 11 |
antidepressant | RefBasedMI | Sample data: antidepressant trial | data.frame | 688 | 14 |
asthma | RefBasedMI | Sample data: asthma trial | data.frame | 732 | 5 |
HMD | bage | Components from Human Mortality Database | bage_ssvd | | |
LFP | bage | Components from OECD Labor Force Participation Data | bage_ssvd | | |
deaths | bage | Deaths in Iceland | tbl_df | 5300 | 5 |
divorces | bage | Divorces in New Zealand | tbl_df | 242 | 5 |
expenditure | bage | Per Capita Health Expenditure in the Netherlands, 2003-2011 | tbl_df | 1296 | 4 |
households | bage | People in One-Person households in New Zealand | tbl_df | 528 | 5 |
injuries | bage | Fatal Injuries in New Zealand | tbl_df | 912 | 6 |
us_acc_deaths | bage | Accidental Deaths in the USA | data.frame | 72 | 2 |
dataCompartment4 | rPBK | An example data set with 4 compartment | tbl_df | 21 | 7 |
dataMaleGammarusSingle | rPBK | An example data set with 1 compartment | tbl_df | 22 | 4 |
fitPBK_C4 | rPBK | An example of fitPBK object | fitPBK | | |
Acidity | mixAK | Acidity index of lakes in North-Central Wisconsin | numeric | | |
Enzyme | mixAK | Enzymatic activity in the blood | numeric | | |
Faithful | mixAK | Old Faithful Geyser Data | data.frame | 272 | 2 |
Galaxy | mixAK | Velocities of distant galaxies | numeric | | |
PBC910 | mixAK | Subset of Mayo Clinic Primary Biliary Cholangitis (Cirrhosis) data | data.frame | 918 | 9 |
PBCseq | mixAK | Mayo Clinic Primary Biliary Cholangitis (Cirrhosis), sequential data | data.frame | 1945 | 38 |
SimData | mixAK | Simulated dataset | data.frame | 1157 | 7 |
Tandmob | mixAK | Signal Tandmobiel data | data.frame | 4430 | 156 |
TandmobEmer | mixAK | Signal Tandmobiel data - emergence times | data.frame | 4430 | 91 |
assetReturns | JFE | Data Sets | xts | 2735 | 29 |
macrodata | JFE | Data Sets | xts | 669 | 4 |
rain.feedback.stats | FeedbackTS | Statistics of rain feedback in Australia | data.frame | 88 | 8 |
rain.site.6008 | FeedbackTS | Rainfall data at Callagiddy station | data.frame | 36615 | 5 |
eez_rg | oceanic | Eez Coefficients | sf | 243 | 16 |
port | oceanic | port position | SpatialPolygonsDataFrame | | |
BFactor_zoo_example | BayesianFactorZoo | Simulated Example Dataset *'BFactor_zoo_example'* | list | | |
KnockoffHybrid.example | KnockoffHybrid | Example data for KnockoffHybrid | list | | |
VAR.inv.roots.from.det.cross | VAR.spec | An example 'data.frame' defining a VAR (Vector autoregression) model. | data.frame | 61 | 15 |
VAR.inv.roots.from.eta.ksi.zeta | VAR.spec | An example 'data.frame' defining a VAR model. | data.frame | 61 | 15 |
data1 | speedglm | A toy dataset | data.frame | 100 | 4 |
Matches | EUfootball | Dataset Matches | data.frame | 24208 | 32 |
breast.17 | bspmma | Aspirin and Breast Cancer: 17 studies | data.frame | 17 | 2 |
caprie.3grps | bspmma | CAPRIE Study: Three Risk Groups | data.frame | 3 | 3 |
ddtm.s | bspmma | Decontamination of the Digestive Tract Mortality, Short Dataset | data.frame | 14 | 4 |
Bundesliga | wikibooks | Results and fixtures of the german football-league "Bundesliga" | data.frame | 13406 | 10 |
Essen.Zeit | wikibooks | How long does it take to give food in nursing home | data.frame | 63 | 22 |
Mikrolagerung | wikibooks | pressure at sacral-bone: 30 degree vs. micro-positioning | data.frame | 98 | 21 |
bsp1 | wikibooks | Datatable of Example 1 | data.frame | 10 | 4 |
bsp2 | wikibooks | Datatable of Example 2 | data.frame | 20 | 2 |
bsp3 | wikibooks | Datatable of Example 3 | data.frame | 14 | 2 |
bsp4 | wikibooks | Datatable of Example 4 | data.frame | 7 | 4 |
cms | wikibooks | Dataset of an assessment instrument | data.frame | 620 | 2 |
Control | TTCA | Control time course | data.frame | 5000 | 11 |
EGF | TTCA | EGF time course data | data.frame | 5000 | 16 |
annot | TTCA | Data file annot | data.frame | 5000 | 2 |
annotation | TTCA | Data file annotation | data.frame | 5000 | 2 |
COVID19_JanApr2020_HongKong | modelSSE | A dataset of COVID-19 outbreak in Hong Kong | data.frame | 290 | 2 |
MERS_2013_MEregion | modelSSE | A dataset of MERS outbreaks in the Middle East region | data.frame | 55 | 3 |
mpox_19801984_DRC | modelSSE | A dataset of mpox outbreaks in DRC | data.frame | 125 | 3 |
smallpox_19581973_Europe | modelSSE | A dataset of smallpox outbreaks in Europe | data.frame | 34 | 3 |
control_clusters | ivdesign | 100 matched control clusters | data.frame | 100 | 14 |
encouraged_clusters | ivdesign | 100 matched encouraged clusters | data.frame | 100 | 14 |
congress | ClusVis | Real categorical data set: Congressional Voting Records Data Set | data.frame | 435 | 17 |
gazelleRelocations | SyncMove | Relocations of Mongolian Gazelles | data.frame | 1747 | 5 |
fat2Lpoly.allSNPs | fat2Lpoly | Example results output by the function 'fat2Lpoly.withinR' | list | | |
ped.x.all | fat2Lpoly | Example dataset returned by the function 'read.merlin.files' | list | | |
DowJones | Copula.Markov | Dow Jones Industrial Average | data.frame | 754 | 1 |
polio | weightedCL | Polio cases in USA from Jan 1970 till Dec 1983 | numeric | | |
sleep | weightedCL | Infant sleep status data | data.frame | 1024 | 3 |
ACEdata | hapsim | ACE data set | data.frame | 22 | 52 |
county_bins | binequality | A data set containing binned income for US counties | data.frame | 51536 | 11 |
school_district_bins | binequality | A data set containing the school district data. | list | | |
state_bins | binequality | A data set containing the binned state data. | data.frame | 832 | 8 |
moore | PAmeasures | Moore's Law data | data.frame | 48 | 3 |
Hedenfalk | Equalden.HD | Hedenfalk data | matrix | 3226 | 15 |
Rat | Equalden.HD | Rat data | data.frame | 8038 | 5 |
cdc_state_counts | excessmort | Weekly death counts for each USA state | tbl_df | 13023 | 5 |
cook_demographics | excessmort | Cook County Medical Examiner Records | tbl_df | 470700 | 5 |
cook_records | excessmort | Cook County Medical Examiner Records | tbl_df | 58138 | 7 |
icd | excessmort | Puerto Rico daily mortality by cause of death | spec_tbl_df | 31 | 2 |
louisiana_counts | excessmort | Louisiana daily mortality | tbl_df | 1461 | 3 |
new_jersey_counts | excessmort | New Jersey daily mortality | tbl_df | 3287 | 3 |
puerto_rico_counts | excessmort | Puerto Rico daily mortality | tbl_df | 567084 | 5 |
puerto_rico_icd | excessmort | Puerto Rico daily mortality by cause of death | tbl_df | 251940 | 4 |
world_counts | excessmort | Weekly death counts for several countries | tbl_df | 21844 | 4 |
age.income | SemiPar | Age/income data | data.frame | 205 | 2 |
bpd | SemiPar | Bronchopulmonary dysplasia data | data.frame | 223 | 2 |
calif.air.poll | SemiPar | California air polution data | data.frame | 345 | 4 |
copper | SemiPar | Copper data | data.frame | 442 | 8 |
elec.temp | SemiPar | Electricity usage and temperature data | data.frame | 55 | 2 |
ethanol | SemiPar | Ethanol data | data.frame | 88 | 3 |
fossil | SemiPar | Fossil data | data.frame | 106 | 2 |
fuel.frame | SemiPar | Automobile data from consumer reports | data.frame | 60 | 6 |
janka | SemiPar | Janka hardness data | data.frame | 36 | 2 |
lidar | SemiPar | LIDAR data | data.frame | 221 | 2 |
milan.mort | SemiPar | Milan mortality data | data.frame | 3652 | 9 |
monitor.mercury | SemiPar | Mercury biomonintoring data | data.frame | 22 | 3 |
onions | SemiPar | Onions data | data.frame | 84 | 3 |
pig.weights | SemiPar | Pig weight data | data.frame | 432 | 3 |
ragweed | SemiPar | Ragweed data | data.frame | 335 | 6 |
retire.plan | SemiPar | Retirement plan data | data.frame | 92 | 10 |
salinity | SemiPar | Salinity data | data.frame | 28 | 4 |
sausage | SemiPar | Sausage data | data.frame | 54 | 3 |
scallop | SemiPar | Scallop abundance data | data.frame | 148 | 3 |
sitka | SemiPar | Sitka spruce data | data.frame | 1027 | 5 |
term.structure | SemiPar | Term structure data | data.frame | 117 | 2 |
trade.union | SemiPar | Trade union data | data.frame | 534 | 11 |
ustemp | SemiPar | U.S. temperature data | data.frame | 56 | 4 |
docvisits | zic | Demand for Health Care Data | data.frame | 1812 | 23 |
DecodeMap | IBDsim | Decode recombination map | list | | |
dominant1 | IBDsim | Autosomal dominant pedigree | matrix | 14 | 6 |
bhpm.cluster.data1 | bhpm | Cluster analysis data. | data.frame | 1860 | 6 |
bhpm.cluster.data2 | bhpm | Cluster analysis data. | data.frame | 3100 | 6 |
bhpm.multi.treatments | bhpm | Cluster analysis data. | data.frame | 3720 | 6 |
bhpm.multi.treatments.random.order | bhpm | Cluster analysis data. | data.frame | 3720 | 6 |
bde9915 | tsoutliers | Data Set: Working Paper 'bde9915' | list | | |
hicp | tsoutliers | Data Set: Harmonised Indices of Consumer Prices | list | | |
ipi | tsoutliers | Data Set: Industrial Production Indices | list | | |
AirBcn | TSTutorial | Monthly Airline Passenger Numbers 1990-2009 of Barcelona | ts | | |
Turismes | TSTutorial | Monthly Made Vehicles in Spain 1990-2008. | ts | | |
Victimes | TSTutorial | Monthly Traffic Deads Number 1993-2008 of Spain. | ts | | |
burposte | frontiles | Burposte data | data.frame | 9521 | 3 |
spain | frontiles | Spain data | data.frame | 61 | 4 |
EDpro | PROreg | Eating Disorders patient-reported outcome data. | data.frame | 525 | 18 |
SP500FTSElr | costat | Log-returns time series of the SP500 and FTSE100 indices | data.frame | 2048 | 3 |
fret | costat | Particular section of FTSE log-return series. | numeric | | |
sret | costat | Particular section of SP500 log-returns series. | numeric | | |
AsbestosData | cabootcrs | Asbestos data | data.frame | 5 | 4 |
AttachmentData | cabootcrs | van Ijzendoorn's attachment data | data.frame | 4 | 4 |
DreamData | cabootcrs | Maxwell's dream data set, with simplified labels | data.frame | 5 | 4 |
DreamData223by3 | cabootcrs | Maxwell's dream data set with added totally random column | data.frame | 223 | 3 |
DreamDataNames | cabootcrs | Maxwell's dream data set, using full original labels | data.frame | 5 | 4 |
NishData | cabootcrs | Nishisato's Singapore data | data.frame | 23 | 4 |
OsteoData | cabootcrs | Osteoarchaeological data with categories given as numbers | data.frame | 6027 | 11 |
OsteoDataNames | cabootcrs | Osteoarchaeological data with named categories | data.frame | 6027 | 11 |
SuicideData | cabootcrs | Suicide data | data.frame | 34 | 9 |
aphid | aster | Life History Data on Uroleucon rudbeckiae | data.frame | 378 | 4 |
beta.true | aster | Simulated Life History Data | numeric | | |
chamae | aster | Life History Data on Chamaecrista fasciculata | data.frame | 6705 | 8 |
chamae2 | aster | Life History Data on Chamaecrista fasciculata | data.frame | 4478 | 8 |
chamae3 | aster | Life History Data on Chamaecrista fasciculata | data.frame | 19062 | 11 |
echin2 | aster | Life History Data on Echinacea angustifolia | data.frame | 6127 | 9 |
echinacea | aster | Life History Data on Echinacea angustifolia | data.frame | 570 | 12 |
fam | aster | Simulated Life History Data | numeric | | |
fam | aster | Simulated Life History Data | numeric | | |
ladata | aster | Simulated Life History Data | data.frame | 500 | 3 |
mu.true | aster | Simulated Life History Data | numeric | | |
oats | aster | Life History Data on Avena barbata | data.frame | 1642 | 11 |
phi.true | aster | Simulated Life History Data | numeric | | |
pred | aster | Simulated Life History Data | numeric | | |
pred | aster | Simulated Life History Data | numeric | | |
radish | aster | Life History Data on Raphanus sativus | data.frame | 858 | 11 |
redata | aster | Simulated Life History Data | data.frame | 1200 | 7 |
redata | aster | Simulated Life History Data | data.frame | 10000 | 6 |
theta.true | aster | Simulated Life History Data | numeric | | |
vars | aster | Simulated Life History Data | character | | |
vars | aster | Simulated Life History Data | character | | |
wedEth | treebalance | Wedderburn Etherington numbers (from OEIS) | numeric | | |
CVD_Accidents | multipleNCC | Causes of death in three counties in Norway in 1974-2000 | data.frame | 3933 | 16 |
LF.data | LogicForest | LF.data | data.frame | 200 | 52 |
. | freealg | Class "dot" | dot | | |
specdat | LCF | Phosphorus K-edge XANES spectral data for LCF | list | | |
pseudos | changepointTests | Pseudo-observations | matrix | 502 | |
crops | IPEC | Whole-plant biomass Data of 12 Species of Crops | data.frame | 3540 | 6 |
isom | IPEC | Data on Biochemical Oxygen Demand | data.frame | 24 | 4 |
leaves | IPEC | Leaf Data of _Parrotia subaequalis_ (Hamamelidaceae) | data.frame | 1506 | 4 |
shoots | IPEC | Height Growth Data of Bamboo Shoots | data.frame | 147 | 4 |
strings | opencpu | OpenCPU Single-User Server | character | | |
IR90s | amen | International relations in the 90s | list | | |
YX_bin | amen | binary relational data and covariates | list | | |
YX_bin_long | amen | binary relational data and covariates | list | | |
YX_cbin | amen | Censored binary nomination data and covariates | list | | |
YX_frn | amen | Fixed rank nomination data and covariates | list | | |
YX_nrm | amen | normal relational data and covariates | list | | |
YX_ord | amen | ordinal relational data and covariates | list | | |
YX_rrl | amen | row-specific ordinal relational data and covariates | list | | |
addhealthc3 | amen | AddHealth community 3 data | list | | |
addhealthc9 | amen | AddHealth community 9 data | list | | |
coldwar | amen | Cold War data | list | | |
comtrade | amen | Comtrade data | array | | |
dutchcollege | amen | Dutch college data | list | | |
lazegalaw | amen | Lazega's law firm data | list | | |
sampsonmonks | amen | Sampson's monastery data | array | | |
sheep | amen | Sheep dominance data | list | | |
Dforimpute | DDPNA | a data used for Dataimpute function. | list | | |
ProteomicData | DDPNA | Small example proteomic quantification data extract from txt or csv file used to demonstrate data extract function. | list | | |
Sample_ID_data | DDPNA | A small uniprot ID information used to do ID convert in example. | list | | |
imputedData | DDPNA | an imputed data used for downstream analysis | proteomic_data | | |
net | DDPNA | A network which is obtained by WGCNA-package blockwiseModule function. it can short the time of Module analysis example time. | list | | |
trendyExampleData | Trendy | Example dataset for Trendy | matrix | 50 | 40 |
data_example_intelligibility_by_length | wisclabmisc | Simulated intelligibility scores by utterance length | tbl_df | 694 | 5 |
data_fake_intelligibility | wisclabmisc | Fake intelligibility data | tbl_df | 200 | 2 |
data_fake_rates | wisclabmisc | Fake speaking rate data | tbl_df | 200 | 2 |
data_features_consonants | wisclabmisc | Phonetic features of consonants and vowels | tbl_df | 24 | 10 |
data_features_vowels | wisclabmisc | Phonetic features of consonants and vowels | tbl_df | 17 | 12 |
pbmc_small | SeuratObject | A small example version of the PBMC dataset | Seurat | | |
snp | abcrf | A simulated example in population genetics | list | | |
snp.obs | abcrf | A simulated example in population genetics | data.frame | 2 | 48 |
four_image_data | littlelisteners | Example data from a Visual World experiment | tbl_df | 20910 | 25 |
Modules | NetWeaver | Example Module Dataset | data.frame | 50 | 30 |
ucsc.hg19.cytoband | NetWeaver | Human chromosome cytoband | data.frame | 862 | 5 |
ucsc.hg38.cytoband | NetWeaver | Human chromosome cytoband | data.frame | 862 | 5 |
ecosent | grafzahl | A Corpus Of Dutch News Headlines | data.frame | 6322 | 4 |
supported_model_types | grafzahl | Supported model types | character | | |
unciviltweets | grafzahl | A Corpus Of Tweets With Incivility Labels | corpus | | |
oxygen | kwb.resilience | Simulated Dissolved Oxygen in River Spree | data.frame | 23425 | 5 |
boonah | cropgrowdays | SILO weather data extracted for Boonah SE Queensland | tbl_df | 517 | 10 |
crop | cropgrowdays | Crop data containing hypothetical sowing flowering and harvest dates | tbl_df | 10 | 3 |
two_sites | cropgrowdays | SILO weather data extracted for two arbitrary sites | tbl_df | 10 | 11 |
default_cdisc_join_keys | teal.data | List containing default joining keys for 'CDISC' datasets | join_keys | | |
rADAE | teal.data | Random adverse events | tbl_df | 1934 | 92 |
rADCM | teal.data | Random concomitant medications | tbl_df | 3685 | 83 |
rADEX | teal.data | Random response | tbl_df | 6400 | 79 |
rADLB | teal.data | Random lab analysis | tbl_df | 8400 | 102 |
rADRS | teal.data | Random response | tbl_df | 3200 | 65 |
rADSL | teal.data | Random patient listing | tbl_df | 400 | 55 |
rADTR | teal.data | Random data 'rADTR' | data.frame | 2800 | 76 |
rADTTE | teal.data | Random time to event analysis dataset | tbl_df | 2000 | 67 |
rADVS | teal.data | Random data 'rADVS' | tbl_df | 16800 | 87 |
Batselier | mfpp | Real-life project database by Batselier and Vanhoucke (2015) | Collection_PDM | | |
Boctor | mfpp | Sumulated project database by Boctor (1993) | Collection_PDM | | |
MICS2014HL | PakPMICS2014HL | Multiple Indicator Cluster Survey (MICS) 2014 Household Listing Questionnaire Data for Punjab, Pakistan | data.table | 246501 | 81 |
BCI.env | BiodiversityR | Barro Colorado Island Quadrat Descriptions | data.frame | 50 | 7 |
CucurbitaClim | BiodiversityR | Baseline and Future WorldClim 2.1 Climatic Data for Cucurbita Species | data.frame | 2404 | 24 |
faramea | BiodiversityR | Faramea occidentalis abundance in Panama | data.frame | 45 | 8 |
ifri | BiodiversityR | Example data from the International Forestry Resources and Institutions (IFRI) research network | data.frame | 486 | 5 |
transfgradient | BiodiversityR | Gradient for Hypothetical Example of Turover of Species Composition | data.frame | 19 | 1 |
transfspecies | BiodiversityR | Hypothetical Example of Turover of Species Composition | data.frame | 19 | 9 |
warcom | BiodiversityR | Warburgia ugandensis AFLP Scores | data.frame | 100 | 185 |
warenv | BiodiversityR | Warburgia ugandensis Population Structure | data.frame | 100 | 4 |
hg_cytoBandIdeo | chromPlot | cytoBandIdeo human | data.frame | 862 | 5 |
hg_gap | chromPlot | Human Gap | data.frame | 457 | 4 |
mm10_cytoBandIdeo | chromPlot | cytoBandIdeo | data.frame | 448 | 5 |
mm10_gap | chromPlot | Gaps | data.frame | 686 | 4 |
agree_cat | catSurv | Agreeableness Cat Object | Cat | | |
consc_cat | catSurv | Conscientiousness Cat Object | Cat | | |
empathy_cat | catSurv | Empathizing Quotient Cat Object | Cat | | |
ex_qualtrics_results | catSurv | Example Qualtrics Data for Adaptive Inventory | data.frame | 6 | 9 |
ex_qualtrics_results_multiple | catSurv | Example Qualtrics Data for Multiple Adaptive Inventories | data.frame | 6 | 17 |
extra_cat | catSurv | Extraversion Cat Object | Cat | | |
gpcm_cat | catSurv | gpcm Cat Object | Cat | | |
grm_cat | catSurv | grm Cat Object | Cat | | |
ltm_cat | catSurv | ltm Cat Object | Cat | | |
mach_cat | catSurv | Machiavellianism Personality Cat Object | Cat | | |
neuro_cat | catSurv | Neuroticism Cat Object | Cat | | |
nfa_cat | catSurv | Need for Affect Cat Object | Cat | | |
nfc | catSurv | Need For Cognition | data.frame | 4043 | 18 |
nfc_cat | catSurv | Need for Cognition Cat Object | Cat | | |
npi | catSurv | Narcissistic Personality Inventory | data.frame | 11243 | 40 |
npi_battery | catSurv | Narcissistic personality inventory question items | list | | |
npi_cat | catSurv | Narcissistic Personality Cat Object | Cat | | |
nte | catSurv | Need to Evaluate | data.frame | 4005 | 16 |
nte_cat | catSurv | Need to Evaluate Cat Object | Cat | | |
open_cat | catSurv | Openness to Experience Cat Object | Cat | | |
polknowMT | catSurv | MTurk Political Knowledge | data.frame | 810 | 64 |
polknowOrdered | catSurv | TAPS Political Knowledge (Ordered Response Options) | data.frame | 1340 | 10 |
polknowTAPS | catSurv | TAPS Political Knowledge | data.frame | 1496 | 10 |
rwa_cat | catSurv | Right Wing Authoritarianism Cat Object | Cat | | |
sdo_cat | catSurv | Social Dominance Orientation Cat Object | Cat | | |
sv_conservation_cat | catSurv | Conservation (Schwartz Values) Cat Object | Cat | | |
sv_open_cat | catSurv | Openness to Change (Schwartz Values) Cat Object | Cat | | |
sv_selfenhance_cat | catSurv | Self-Enhancement (Schwartz Values) Cat Object | Cat | | |
sv_selftransc_cat | catSurv | Self-Transcendence (Schwartz Values) Cat Object | Cat | | |
systemizing_cat | catSurv | Systemizing Quotient Cat Object | Cat | | |
tpm_cat | catSurv | tpm Cat Object | Cat | | |
paramsMWR | MassWateR | Master parameter list and units for Characteristic Name column in results data | tbl_df | 43 | 4 |
thresholdMWR | MassWateR | Master thresholds list for analysis of results data | tbl_df | 28 | 10 |
BTsubset_data | BioTIMEr | BioTIME subset | data.frame | 81084 | 17 |
BTsubset_meta | BioTIMEr | BioTIME subset metadata | data.frame | 12 | 25 |
datosabiertos | covidmx | Datos abiertos de COVID-19 | list | | |
d.error | frscore | Simulated data of sixteen cases with measurement error in one case | data.frame | 16 | 5 |
income | kernlab | Income Data | data.frame | 8993 | 14 |
musk | kernlab | Musk data set | data.frame | 476 | 167 |
promotergene | kernlab | E. coli promoter gene sequences (DNA) | data.frame | 106 | 58 |
reuters | kernlab | Reuters Text Data | list | | |
rlabels | kernlab | Reuters Text Data | factor | | |
spam | kernlab | Spam E-mail Database | data.frame | 4601 | 58 |
spirals | kernlab | Spirals Dataset | matrix | 300 | |
ticdata | kernlab | The Insurance Company Data | data.frame | 9822 | 86 |
basicdata | gfoRmula | Example Dataset for a Survival Outcome with Censoring | data.table | 11332 | 8 |
basicdata_nocomp | gfoRmula | Example Dataset for a Survival Outcome without Censoring | data.table | 13170 | 7 |
binary_eofdata | gfoRmula | Example Dataset for a Binary Outcome at End of Follow-Up | data.table | 17500 | 7 |
censor_data | gfoRmula | Example Dataset for a Survival Outcome with an Indicator of Censoring Variable | data.table | 118725 | 6 |
continuous_eofdata | gfoRmula | Example Dataset for a Continuous Outcome at End of Follow-Up | data.table | 17500 | 7 |
continuous_eofdata_pb | gfoRmula | Example Dataset for a Continuous Outcome at End of Follow-Up with Pre-Baseline Times | data.table | 22500 | 7 |
aspirin | stepp | The aspirin data set. | data.frame | 1121 | 5 |
balance_example | stepp | Sample data to use with the 'balance_patients()' function. | data.frame | 5000 | 1 |
bigCI | stepp | The BIG 1-98 trial dataset for cumulative incidence STEPP. | data.frame | 2685 | 4 |
bigKM | stepp | The BIG 1-98 trial dataset for Kaplan-Meier STEPP. | data.frame | 2685 | 4 |
simdataKM | stepp | Simulated data for Kaplan-Meier STEPP analysis. | data.frame | 1000 | 4 |
sampleSWCRTLarge | geeCRT | simulated large SW-CRT data | data.frame | 1508 | 10 |
sampleSWCRTSmall | geeCRT | simulated small SW-CRT data | data.frame | 373 | 9 |
ABdata | pdynmc | Employment, wages, capital, and output for companies based in the UK | data.frame | 1031 | 7 |
cigDemand | pdynmc | Cigarette consumption in the US | data.frame | 528 | 9 |
raccoon | sftrack | Movements of two raccoons in an urban park in Florida | data.frame | 445 | 8 |
dict_acs1_geocomponent | totalcensus | List of geographic components used in ACS 1 year surverys | data.table | 28 | 9 |
dict_acs1_summarylevel | totalcensus | List of summary levels used in ACS 1 year surverys | data.table | 23 | 5 |
dict_acs1_table | totalcensus | List of summary levels used in ACS 1 year surverys | data.table | 1818 | 18 |
dict_acs5_geocomponent | totalcensus | List of geographic components used in ACS 5 year surverys | data.table | 19 | 4 |
dict_acs5_summarylevel | totalcensus | List of summary levels used in ACS 5 year surveys | data.table | 87 | 8 |
dict_acs5_table | totalcensus | List of summary levels used in ACS 5 year surverys | data.table | 1183 | 16 |
dict_acs_geoheader_2005_1year | totalcensus | List of geographic headers used in 2005 ACS 1 year survey | data.table | 35 | 4 |
dict_acs_geoheader_2006_2008_1year | totalcensus | List of geographic headers used in 2006 - 2008 ACS 1 year survey | data.table | 51 | 4 |
dict_acs_geoheader_2009_1year | totalcensus | List of geographic headers in 2009 ACS 1 year survey | data.table | 50 | 4 |
dict_acs_geoheader_2009_5year | totalcensus | List of geographic headers used in ACS 5 year survey ending 2009 | data.table | 51 | 4 |
dict_acs_geoheader_2010 | totalcensus | List of geographic headers used in 2010 ACS 1 and 5 year surveys | data.table | 53 | 4 |
dict_acs_geoheader_2011_now | totalcensus | List of geographic headers used in American Community Survey since 2011 | data.table | 53 | 4 |
dict_all_geocomponent_2000 | totalcensus | List of all geographic components, 2000 version | data.table | 99 | 2 |
dict_all_geocomponent_2010 | totalcensus | List of all geographic components, 2010 version | data.table | 114 | 2 |
dict_all_summarylevel | totalcensus | List of all summary levels | data.table | 216 | 2 |
dict_cbsa | totalcensus | List CBSA code of Metropolitan Statistical Area/Micropolitan Statistical Area | data.table | 1882 | 12 |
dict_decennial_geocomponent_2000 | totalcensus | List of geographic components and codes in census 2000 | data.table | 98 | 4 |
dict_decennial_geocomponent_2010 | totalcensus | List of geographic components and codes in census 2010 | data.table | 96 | 4 |
dict_decennial_geoheader_2000 | totalcensus | List of geographic headers in census 2000 | data.table | 83 | 4 |
dict_decennial_geoheader_2010 | totalcensus | List of geographic headers in census 2010 | data.table | 101 | 4 |
dict_decennial_summarylevel_2000 | totalcensus | Summary levels available in Census 2000 | data.table | 114 | 4 |
dict_decennial_summarylevel_2010 | totalcensus | Summary levels available in Census 2010 | data.table | 165 | 4 |
dict_decennial_table_2000 | totalcensus | Complete list of 2000 census tables | data.table | 286 | 4 |
dict_decennial_table_2010 | totalcensus | Complete list of 2010 census tables | data.table | 333 | 4 |
dict_fips | totalcensus | List of FIPS code as of 2016 in the US | data.table | 43934 | 9 |
lookup_acs1year_2005 | totalcensus | ACS 1-year 2005 file segment and table lookup data | data.table | 27106 | 7 |
lookup_acs1year_2006 | totalcensus | ACS 1-year 2006 file segment and table lookup data | data.table | 27986 | 3 |
lookup_acs1year_2007 | totalcensus | ACS 1-year 2007 file segment and table lookup data | data.table | 29709 | 3 |
lookup_acs1year_2008 | totalcensus | ACS 1-year 2008 file segment and table lookup data | data.table | 30403 | 3 |
lookup_acs1year_2009 | totalcensus | ACS 1-year 2009 file segment and table lookup data | data.table | 34408 | 3 |
lookup_acs1year_2010 | totalcensus | ACS 1-year 2010 file segment and table lookup data | data.table | 35081 | 3 |
lookup_acs1year_2011 | totalcensus | ACS 1-year 2011 file segment and table lookup data | data.table | 34454 | 3 |
lookup_acs1year_2012 | totalcensus | ACS 1-year 2012 file segment and table lookup data | data.table | 34394 | 3 |
lookup_acs1year_2013 | totalcensus | ACS 1-year 2013 file segment and table lookup data | data.table | 32752 | 3 |
lookup_acs1year_2014 | totalcensus | ACS 1-year 2014 file segment and table lookup data | data.table | 31561 | 3 |
lookup_acs1year_2015 | totalcensus | ACS 1-year 2015 file segment and table lookup data | data.table | 31600 | 3 |
lookup_acs1year_2016 | totalcensus | ACS 1-year 2016 file segment and table lookup data | data.table | 31683 | 3 |
lookup_acs1year_2017 | totalcensus | ACS 1-year 2017 file segment and table lookup data | data.table | 33593 | 3 |
lookup_acs1year_2018 | totalcensus | ACS 1-year 2018 file segment and table lookup data | data.table | 35502 | 3 |
lookup_acs1year_2019 | totalcensus | ACS 1-year 2019 file segment and table lookup data | data.table | 35527 | 3 |
lookup_acs5year_2009 | totalcensus | ACS 5-year 2009 file segment and table lookup data | data.table | 21207 | 7 |
lookup_acs5year_2010 | totalcensus | ACS 5-year 2010 file segment and table lookup data | data.table | 21487 | 7 |
lookup_acs5year_2011 | totalcensus | ACS 5-year 2011 file segment and table lookup data | data.table | 21038 | 7 |
lookup_acs5year_2012 | totalcensus | ACS 5-year 2012 file segment and table lookup data | data.table | 22527 | 7 |
lookup_acs5year_2013 | totalcensus | ACS 5-year 2013 file segment and table lookup data | data.table | 22711 | 7 |
lookup_acs5year_2014 | totalcensus | ACS 5-year 2014 file segment and table lookup data | data.table | 22627 | 7 |
lookup_acs5year_2015 | totalcensus | ACS 5-year 2015 file segment and table lookup data | data.table | 22767 | 7 |
lookup_acs5year_2016 | totalcensus | ACS 5-year 2016 file segment and table lookup data | data.table | 22815 | 7 |
lookup_acs5year_2017 | totalcensus | ACS 5-year 2017 file segment and table lookup data | data.table | 25070 | 7 |
lookup_acs5year_2018 | totalcensus | ACS 5-year 2018 file segment and table lookup data | data.table | 26996 | 7 |
lookup_acs5year_2019 | totalcensus | ACS 5-year 2019 file segment and table lookup data | data.table | 27039 | 7 |
lookup_acs5year_2020 | totalcensus | ACS 5-year 2020 file segment and table lookup data | data.table | 27850 | 7 |
lookup_acs5year_2021 | totalcensus | ACS 5-year 2021 file segment and table lookup data | data.table | 27886 | 7 |
lookup_decennial_2000 | totalcensus | Lookup data files and table contents of Census 2000 | data.table | 8321 | 6 |
lookup_decennial_2010 | totalcensus | Lookup data files and table contents of Census 2010 | data.table | 9199 | 6 |
states_DC | totalcensus | Vector of the abbreviations of 50 states and DC | character | | |
table_content_acs1year_all_years | totalcensus | ACS 1-year table contents of all years | data.table | 44137 | 19 |
CreditMDR | DiSSMod | Credit cards derogatory reports data | data.frame | 13444 | 8 |
DoctorRWM | DiSSMod | German doctor first visits data | data.frame | 7293 | 26 |
NSCLC | ThresholdROCsurvival | Non-small cell lung cancer (NSCLC) data | data.frame | 203 | 4 |
hnscc | highMLR | High dimensional head and neck cancer survival and gene expression data | data.frame | 565 | 104 |
srdata | highMLR | High dimensional protein gene expression data | data.frame | 288 | 250 |
WDI_data | WDI | World Development Indicators series and country information | list | | |
examples | mri | Examples of Misclassifications of Units | list | | |
dataCopCont | REndo | Simulated Dataset with One Endogenous Continuous Regressor | data.frame | 2500 | 4 |
dataCopCont2 | REndo | Simulated Dataset with Two Endogenous Continuous Regressor | data.frame | 2500 | 5 |
dataCopDis | REndo | Simulated Dataset with One Endogenous Discrete Regressor | data.frame | 2500 | 4 |
dataCopDis2 | REndo | Simulated Dataset with Two Endogenous Discrete Regressors | data.frame | 2500 | 5 |
dataCopDisCont | REndo | Simulated Dataset with Two Endogenous Regressors | data.frame | 2500 | 5 |
dataHetIV | REndo | Simulated Dataset with One Endogenous Continuous Regressor | data.frame | 2500 | 4 |
dataHigherMoments | REndo | Simulated Dataset with One Endogenous Regressor | data.frame | 2500 | 4 |
dataLatentIV | REndo | Simulated Dataset with One Endogenous Continuous Regressor | data.frame | 2500 | 3 |
dataMultilevelIV | REndo | Multilevel Simulated Dataset - Three Levels | data.frame | 2767 | 15 |
lsa | eatRep | Achievement data from two large-scale assessments of 2010 and 2015. | data.frame | 77322 | 25 |
cophe_multi_trait_data | cophescan | Simulated multi-trait data | list | | |
CDEC.snow.courses | sharpshootR | CDEC Snow Course List | data.frame | 259 | 9 |
HHM | sharpshootR | Highland Meadows | data.frame | 3469 | 12 |
OSDexamples | sharpshootR | Example output from soilDB::fetchOSD() | list | | |
amador | sharpshootR | SSURGO Data Associated with the Amador Soil Series | data.frame | 42 | 3 |
plssMeridians | sharpshootR | LL2PLSS | data.frame | 87 | 3 |
table5.2 | sharpshootR | Table 5.2 from Hole and Campbell, 1985. | matrix | 18 | 18 |
DRES | dySEM | Relationship quality and sexual satisfaction of 121 couples | data.frame | 121 | 28 |
commitmentM | dySEM | Ratings of relational satisfaction and commitment from 282 (M)ixed-sex couples | data.frame | 282 | 20 |
commitmentQ | dySEM | Ratings of relational satisfaction and commitment from 282 (Q)ueer couples | data.frame | 118 | 20 |
COVID | ggHoriPlot | Distribution of COVID-19 cases in Asia | tbl_df | 12695 | 3 |
climate_CPH | ggHoriPlot | Average temperature in Copenhagen | spec_tbl_df | 9132 | 9 |
climate_US | ggHoriPlot | Average temperature in major cities of the US | spec_tbl_df | 57828 | 9 |
rmsk | ggHoriPlot | Distribution of repeats along the human genome | grouped_df | 30885 | 4 |
sports_time | ggHoriPlot | Peaks times for sports and leisure activities | tbl_df | 8092 | 3 |
gadarian | stmgui | Gadarian and Albertson data | data.frame | 341 | 4 |
AgeS | BayLum | Output of 'AgeS_Computation' function for the samples: "GDB5" and "GDB3" | list | | |
DATA1 | BayLum | DATA of sample named GDB3 | list | | |
DATA2 | BayLum | DATA on sample named GDB5 | list | | |
DATA3 | BayLum | DATA of sample named FER1 | list | | |
DATA_C14 | BayLum | C14 cal age estiamte and its error | list | | |
IntCal13 | BayLum | Atmospheric North data for calibration of 14C age | data.frame | 5141 | 3 |
IntCal20 | BayLum | Atmospheric North data for calibration of 14C age | data.frame | 9501 | 3 |
MCMCsample | BayLum | MCMC sample from the posterior distribution of the dataset GDB5 | matrix | 6000 | 3 |
Marine13 | BayLum | Marine data for calibration of 14C age | data.frame | 4801 | 3 |
Marine20 | BayLum | Marine data for calibration of 14C age | data.frame | 5501 | 3 |
ModelC14 | BayLum | Likelihood of C14 samples for JAGS models use in 'Age_OSLC14' | list | | |
ModelOSL | BayLum | Likelihood of OSL samples for JAGS models use in 'Age_OSLC14' | list | | |
ModelPrior | BayLum | Prior for JAGS models use in 'Age_OSLC14' | list | | |
Model_Age | BayLum | JAGS models use in 'Age_Computation' | list | | |
Model_AgeC14 | BayLum | JAGS models use in 'AgeC14_Computation' | list | | |
Model_AgeS | BayLum | JAGS models use in 'AgeS_Computation' | list | | |
Model_Palaeodose | BayLum | JAGS models use in 'Palaeodose_Computation' | list | | |
SHCal13 | BayLum | Atmospheric South data for calibration of 14C age | data.frame | 5141 | 3 |
SHCal20 | BayLum | Atmospheric South data for calibration of 14C age | data.frame | 9501 | 3 |
sample | sandbox | Example Grain Size Data | data.frame | 1000 | 12 |
sample_osl_aliquots | sandbox | Aliquots Prepared to Measured Virtually | list | | |
car.test.frame | rpart | Automobile Data from 'Consumer Reports' 1990 | data.frame | 60 | 8 |
car90 | rpart | Automobile Data from 'Consumer Reports' 1990 | data.frame | 111 | 34 |
cu.summary | rpart | Automobile Data from 'Consumer Reports' 1990 | data.frame | 117 | 5 |
kyphosis | rpart | Data on Children who have had Corrective Spinal Surgery | data.frame | 81 | 4 |
solder | rpart | Soldering of Components on Printed-Circuit Boards | data.frame | 900 | 6 |
solder.balance | rpart | Soldering of Components on Printed-Circuit Boards | data.frame | 720 | 6 |
stagec | rpart | Stage C Prostate Cancer | data.frame | 146 | 8 |
cmhc_cma_translation_data | cmhc | A dataset with geographic identifiers for CMHC and Census at the CMA level | tbl_df | 153 | 3 |
cmhc_csd_translation_data | cmhc | A dataset with geographic identifiers for CMHC and Census at the CSD level | tbl_df | 5161 | 4 |
cmhc_csd_translation_data_2023 | cmhc | A dataset with geographic identifiers for CMHC and Census at the CSD level for 2023 data portal version | tbl_df | 918 | 2 |
cmhc_ct_translation_data | cmhc | A dataset with geographic identifiers for CMHC and Census at the CT level | tbl_df | 5934 | 18 |
ABS | rjd3toolkit | | data.frame | 425 | 22 |
Exports | rjd3toolkit | | list | | |
Imports | rjd3toolkit | | list | | |
retail | rjd3toolkit | | list | | |
fuel_mix | kayadata | Mix of fuels contributing to primary energy supply for many countries and regions | tbl_df | 948 | 7 |
kaya_data | kayadata | Kaya identity data for many countries and regions | tbl_df | 5248 | 14 |
td_trends | kayadata | Top-down projections of trends in Kaya variables for many countries and regions | tbl_df | 225 | 11 |
td_values | kayadata | Top-down projections of future Kaya variables for many countries and regions | tbl_df | 3116 | 12 |
PK | guiplot | somedata | data.frame | 26 | 4 |
bnMCMCResults | genMCMCDiag | Results from a Bayesian Network MCMC algorithm on simulated data | list | | |
uniMCMCResults | genMCMCDiag | Results from a univariate MCMC algorithm on a simulated posterior | list | | |
pc | uklr | UK Postcodes and NUTS3 Codes | spec_tbl_df | 1759911 | 2 |
sbd_bdlim | bdlim | Simulated Birth Data | data.frame | 1000 | 202 |
pheno | SoyURT | Phenotype | data.frame | 39006 | 13 |
soil | SoyURT | Soil variables | data.frame | 504 | 5 |
weather | SoyURT | Weather variables | data.frame | 74012 | 25 |
simsolvd | anoint | Simulated SOLVD-Trial data set | data.frame | 2569 | 13 |
templateK40 | handwriterApp | Cluster Template with 40 Clusters | list | | |
templateK8 | handwriterApp | Small Cluster Template with 8 Clusters | list | | |
hgnc2pfam.df | g3viz | Mapping table between gene.symbol, uniprot.id, and pfam | data.frame | 49635 | 8 |
mutation.table.df | g3viz | Default mapping table between mutation type (aka, variant classification) to mutation class | data.frame | 28 | 3 |
kuiper2013 | bain | The Effect of Prior Interaction on Trust | data.frame | 4 | 4 |
sesamesim | bain | Simulated Sesame Street Data | data.frame | 240 | 21 |
synthetic_dk | bain | Simulated data about morality and politics in Denmark | data.frame | 552 | 31 |
synthetic_nl | bain | Simulated data about morality and politics in The Netherlands | data.frame | 401 | 38 |
synthetic_us | bain | Simulated data about morality and politics in the USA | data.frame | 518 | 33 |
mmrm_test_data | tern.mmrm | Example dataset for 'tern.mmrm' package. | tbl_df | 800 | 7 |
fish | occumb | Fish eDNA metabarcoding dataset | occumbData | | |
fish_raw | occumb | Fish eDNA metabarcoding dataset | list | | |
bionet_example | mwcsr | Example MWCS instance obtained from BioNet package tutorial | igraph | | |
gam_example | mwcsr | GAM instance for MWCS problem | igraph | | |
gatom_example | mwcsr | Example of graph from which an SGMWCS instance can be obtained | igraph | | |
gmwcs_example | mwcsr | Example GMWCS instance | igraph | | |
gmwcs_small_instance | mwcsr | Small example of GMWCS instance for demonstration purposes. | igraph | | |
mwcs_example | mwcsr | Example MWCS instance | igraph | | |
mwcs_small_instance | mwcsr | Small example of MWCS instance for demonstration purposes. | igraph | | |
sgmwcs_example | mwcsr | Example SGMWCS instance | igraph | | |
sgmwcs_small_instance | mwcsr | Small example of SGMWCS instance for demonstration purposes. | igraph | | |
Data.Incomes | LorenzRegression | Simulated income data | data.frame | 200 | 7 |
FOCUSprofile | morse | A simulated exposure profile with 11641 time points. | spec_tbl_df | 11641 | 3 |
cadmium1 | morse | Reproduction and survival data sets for _Daphnia magna_ exposed to cadmium during 21 days | data.frame | 200 | 5 |
cadmium2 | morse | Reproduction and survival data sets for _Lymnaea stagnalis_ exposed to cadmium during 28 days | data.frame | 612 | 5 |
chlordan | morse | Reproduction and survival data sets for _Daphnia magna_ exposed to chlordan during 21 days | data.frame | 1320 | 5 |
copper | morse | Reproduction and survival data sets for _Daphnia magna_ exposed to copper during 21 days | data.frame | 240 | 5 |
dichromate | morse | Survival data set for _Daphnia magna_ exposed to dichromate during 21 days | data.frame | 60 | 4 |
propiconazole | morse | Survival data set for _Gammarus pulex_ exposed to propiconazole during four days | data.frame | 40 | 4 |
propiconazole_pulse_exposure | morse | Survival data set for _Gammarus pulex_ exposed to propiconazole during 10 days with time-variable exposure concentration (non-standard pulsed toxicity experiments) | data.frame | 74 | 4 |
propiconazole_split | morse | Survival data set for _Gammarus pulex_ exposed to propiconazole during four days | spec_tbl_df | 80 | 4 |
zinc | morse | Reproduction and survival data sets for _Daphnia magna_ exposed to zinc during 21 days | data.frame | 180 | 5 |
example0 | rgTest | Example | list | | |
employment_matrix | leontief | Employment matrix (2013 data) This matrix contains the employed people by industry and the employment coefficient that is the number of people divided by the total final demand from the wage and demand matrix. | matrix | 12 | 2 |
transaction_matrix | leontief | Transaction matrix (2013 data) This matrix contains the production of the chilean economy divided into 12 industries. The measuring unit is CLP million of the year 2013 | matrix | 12 | 12 |
wage_demand_matrix | leontief | Wage and demand matrix (2013 data) This matrix contains the wage, intermediate demand and disaggregated final demand of the chilean economy divided into 12 industries. The final demand is given by components (household consumption, government consumption, etc.) and aggregated. The measuring unit is CLP million of the year 2013. | matrix | 12 | 9 |
transfers | EpiContactTrace | Movement Example Data | data.frame | 70190 | 6 |
errBalancedF | dada2 | An empirical error matrix. | matrix | 16 | 41 |
errBalancedR | dada2 | An empirical error matrix. | matrix | 16 | 41 |
tperr1 | dada2 | An empirical error matrix. | matrix | 16 | 41 |
aml.sample | flowBin | Multitube AML sample as example data for flowBin | FlowSample | | |
Chipseq_Peak_demo | seq2pathway | chip seq loci data example | data.frame | 5 | 5 |
GRanges_demo | seq2pathway | loci information with GRanges format | GRanges | | |
dat_RNA | seq2pathway | RNA sequence data example | data.frame | 5000 | 5 |
dat_chip | seq2pathway | chip seq data example | data.frame | 639 | 1 |
pasilla | tidySummarizedExperiment | Read counts of RNA-seq samples of Pasilla knock-down by Brooks et al. | SummarizedExperiment | | |
se | tidySummarizedExperiment | Read counts of RNA-seq samples derived from Pasilla knock-down by Brooks et al. | RangedSummarizedExperiment | | |
pbRNAseq | MultimodalExperiment | MultimodalExperiment Example Data | matrix | 3000 | 1 |
scADTseq | MultimodalExperiment | MultimodalExperiment Example Data | matrix | 8 | 5000 |
scRNAseq | MultimodalExperiment | MultimodalExperiment Example Data | matrix | 3000 | 5000 |
excludegenes | ASSIGN | Exclude Gene List | character | | |
geneList1 | ASSIGN | Pathway signature gene sets | list | | |
gfrn_geneList | ASSIGN | Pathway Signature Gene Lists | list | | |
testData1 | ASSIGN | Gene expression profiling from cancer patients (test dataset) | data.frame | 1000 | 111 |
trainingData1 | ASSIGN | Gene expression profiling from cell line perturbation experiments (training dataset) | data.frame | 1000 | 55 |
TCsimData | splineTimeR | Simulated time-course gene expression data set | ExpressionSet | | |
hpa_histology_data | HPAanalyze | HPA histology dataset | list | | |
tres_palacios | ldc | Mean daily flow and point E. coli bacteria measurements. | data.frame | 7671 | 4 |
alldata | gunsales | Source data from the FBI's National Instant Criminal Background Check System | tbl_df | 11648 | 35 |
poptotal | gunsales | US Population Growth data | tbl_df | 229 | 3 |
duncan | aspect | Duncan dataset | data.frame | 1204 | 12 |
galo | aspect | GALO dataset | data.frame | 1290 | 5 |
wurzer | aspect | Internet terminals | data.frame | 215 | 8 |
exon.data | xmapbridge | Sample exon array dataset | data.frame | 8888 | 18 |
AOEunits | unheadr | Statistics for game units in Age of Empires II: Definitive Edition | spec_tbl_df | 128 | 19 |
AOEunits_raw | unheadr | Statistics for game units in Age of Empires II: Definitive Edition in a messy presentation | spec_tbl_df | 139 | 15 |
primates2017 | unheadr | Comparative data for 54 species of primates | spec_tbl_df | 69 | 4 |
primates2017_broken | unheadr | Comparative data for 16 species of primates with some broken values | spec_tbl_df | 19 | 4 |
primates2017_wrapped | unheadr | Comparative data for two species of primates | tbl_df | 9 | 6 |
margex | prediction | Artificial data for margins, copied from Stata | tbl_df | 3000 | 11 |
riverforest | ccptm | River Forest, IL, Property Tax Data | data.frame | 1208 | 36 |
mendota | isotone | Number of freezing days at Lake Mendota | data.frame | 12 | 2 |
pituitary | isotone | Size of pituitary fissue | data.frame | 11 | 2 |
posturo | isotone | Repeated posturographic measures | data.frame | 50 | 4 |
observed | pEPA | Sample Panel of Commodities Spot Prices. | matrix | 303 | 56 |
predicted | pEPA | Sample Panels of Commodities Spot Prices Forecasts. | list | | |
carmel | starsExtra | Digital Elevation Model of Mount Carmel | stars | | |
dem | starsExtra | Small Digital Elevation Model | stars | | |
golan | starsExtra | Digital Elevation Model of Golan Heights | stars | | |
landsat | starsExtra | RGB image of Mount Carmel | stars | | |
fertility | Countr | Fertility data | data.frame | 1243 | 9 |
football | Countr | Football data | data.frame | 3040 | 6 |
MenSS | missingHE | MenSS economic data on STIs | data.frame | 159 | 13 |
PBS | missingHE | PBS economic data on intellectual disability and challenging behaviour | data.frame | 732 | 13 |
BLOSUM | DECIPHER | BLOSUM Amino Acid Substitution Matrices | array | | |
HEC_MI1 | DECIPHER | Mutual Information for Protein Secondary Structure Prediction | array | | |
HEC_MI2 | DECIPHER | Mutual Information for Protein Secondary Structure Prediction | array | | |
MIQS | DECIPHER | MIQS Amino Acid Substitution Matrix | matrix | 25 | 25 |
MMLSUM | DECIPHER | MMLSUM Amino Acid Substitution Matrices | array | | |
NonCodingRNA_Archaea | DECIPHER | NonCoding Models for Common Non-Coding RNA Families | list | | |
NonCodingRNA_Bacteria | DECIPHER | NonCoding Models for Common Non-Coding RNA Families | list | | |
NonCodingRNA_Eukarya | DECIPHER | NonCoding Models for Common Non-Coding RNA Families | list | | |
PAM | DECIPHER | PAM Amino Acid Substitution Matrices | array | | |
PFASUM | DECIPHER | PFASUM Amino Acid Substitution Matrices | array | | |
RESTRICTION_ENZYMES | DECIPHER | Common Restriction Enzyme's Cut Sites | character | | |
TrainingSet_16S | DECIPHER | Training Set for Classification of 16S rRNA Gene Sequences | Taxa | | |
deltaGrules | DECIPHER | Free Energy of Hybridization of Probe/Target Quadruplets on Microarrays | array | | |
deltaGrulesRNA | DECIPHER | Pseudoenergy Parameters for RNA Quadruplets | array | | |
deltaHrules | DECIPHER | Change in Enthalpy of Hybridization of DNA/DNA Quadruplets in Solution | array | | |
deltaHrulesRNA | DECIPHER | Change in Enthalpy of Hybridization of RNA/RNA Quadruplets in Solution | array | | |
deltaSrules | DECIPHER | Change in Entropy of Hybridization of DNA/DNA Quadruplets in Solution | array | | |
deltaSrulesRNA | DECIPHER | Change in Entropy of Hybridization of RNA/RNA Quadruplets in Solution | array | | |
lambda | drimmR | lambda genome | SeqFastadna | | |
finalData | EventPredInCure | Final enrollment and event data after achieving the target number of events | tbl_df | 300 | 9 |
interimData1 | EventPredInCure | Interim enrollment and event data before enrollment completion | tbl_df | 224 | 9 |
interimData2 | EventPredInCure | Interim enrollment and event data after enrollment completion | tbl_df | 300 | 9 |
tournament | elo | 'tournament': Mock data for examples | data.frame | 56 | 6 |
tournament.multiteam | elo | 'tournament.multiteam': Mock data for examples | tbl_df | 28 | 6 |
antidep | remiod | wide format of continuous response of antidepressant data. | tbl_df | 172 | 7 |
schizo | remiod | National Institute of Mental Health shizophrenia study | data.table | 3059 | 6 |
schizob | remiod | wide format of binary response of Schizophrenia data. | data.frame | 437 | 5 |
schizow | remiod | wide format of ordinal response of Schizophrenia data. | data.frame | 437 | 5 |
X | Bayenet | simulated data for demonstrating the features of Bayenet. | matrix | 10 | |
Y | Bayenet | simulated data for demonstrating the features of Bayenet. | matrix | 10 | |
clin | Bayenet | simulated data for demonstrating the features of Bayenet. | matrix | 10 | |
coef | Bayenet | simulated data for demonstrating the features of Bayenet. | numeric | | |
carbon.fabric | cmstatr | Sample data for a generic carbon fabric | data.frame | 216 | 5 |
carbon.fabric.2 | cmstatr | Sample data for a generic carbon fabric | data.frame | 177 | 9 |
electricity | ForecastComb | UK Electricity Supply 2007 - 2017 | mts | 123 | 6 |
gpheats | sport | Heat results of Speedway Grand-Prix | data.frame | 21932 | 11 |
gpsquads | sport | Turnament results of Speedway Grand-Prix | data.frame | 4536 | 9 |
iris2 | tablesgg | A Reshaped Version of Anderson's Iris Data | data.frame | 600 | 5 |
iris2_tab | tablesgg | Table of Summary Statistics for Anderson's Iris Data | tabular | 6 | 4 |
mtcars_xtab | tablesgg | Table of Data from Motor Trend Magazine | xtableList | | |
styles_pkg | tablesgg | Built-In Styles for Table Elements | list | | |
tli_xtab | tablesgg | Table of Test Scores and Demographics for 20 Students | xtable | 20 | 5 |
germancredit | scorecard | German Credit Data | data.frame | 1000 | 21 |
colour_aliases_1in1000 | r2dii.colours | Named colour vector associated with 1 in 1000 | character | | |
colour_aliases_2dii | r2dii.colours | Named colour vector associated with 2DII values | character | | |
colour_aliases_pacta | r2dii.colours | Named colour vector associated with PACTA sectors and technologies | character | | |
colour_aliases_survey | r2dii.colours | Named colour vector associated with user survey | character | | |
palette_1in1000_background | r2dii.colours | Colour palette datasets | character | | |
palette_1in1000_goodbad | r2dii.colours | Colour palette datasets | tbl_df | 5 | 2 |
palette_1in1000_plot | r2dii.colours | Colour palette datasets | tbl_df | 10 | 2 |
palette_2dii_automotive | r2dii.colours | Colour palette datasets | tbl_df | 7 | 2 |
palette_2dii_fossil_fuels | r2dii.colours | Colour palette datasets | tbl_df | 3 | 2 |
palette_2dii_oil_gas | r2dii.colours | Colour palette datasets | tbl_df | 2 | 2 |
palette_2dii_plot | r2dii.colours | Colour palette datasets | tbl_df | 9 | 2 |
palette_2dii_power | r2dii.colours | Colour palette datasets | tbl_df | 6 | 2 |
palette_2dii_scenario | r2dii.colours | Colour palette datasets | tbl_df | 5 | 2 |
palette_2dii_sector | r2dii.colours | Colour palette datasets | tbl_df | 8 | 2 |
randomNamesData | randomNames | First names (by gender and ethnicity) and last names (by ethnicity) for randomNames function | environment | | |
Arkansas | SiZer | Time Series of Macroinvertabrates Abundance in the Arkansas River. | data.frame | 90 | 2 |
mbord | aurelhy | A geoshapes object with a polygon of the area to analyze (around Morocco) | geoshapes | | |
mmask | aurelhy | A geomask object masking the Morocco terrain model | geomask | 1998 | |
morocco | aurelhy | A digital elevation model with a grid of roughly 1km x 1km of Morocco | geotm | 1998 | |
mpet | aurelhy | A geopoints object with PET values measured at different weather stations | geopoints | 18 | 39 |
mrain | aurelhy | A geopoints object with normalized rain values (mm) measured at different weather stations | geopoints | 43 | 3 |
mseadist | aurelhy | A geomat object with distance from the sea for the morocco data | geomat | 160 | |
EEGsignal | DFA | A single DFA dataframe with the decimal log fluctuation curve. | data.frame | 91 | 2 |
IXIC2008 | DFA | Time series referring to the adjusted closing price of the NASDAQ Composite (^IXIC) during the United States bear market of 2007-2009 | numeric | | |
LSE.L2008 | DFA | Time series referring to the adjusted closing price of the London Stock Exchange Group plc (LSE.L) during the period which the United States faced the bear market of 2007-2009. | numeric | | |
NYA2008 | DFA | Time series referring to the adjusted closing price of the NYSE COMPOSITE (^NYA) during the United States bear market of 2007-2009 | numeric | | |
SSEC2008 | DFA | Time series referring to the adjusted closing price of the SSE Composite Index (^SSEC) during the period which the United States faced the bear market of 2007-2009. | numeric | | |
lrcorrelation | DFA | data frame with log fluctuation channel curve simulated following an ARFIMA process | data.frame | 40 | 10 |
pnet | spreadr | Small example of a phonological network as an igraph object | igraph | | |
pnetm | spreadr | Small example of a phonological network as an adjacency matrix | matrix | 34 | 34 |
coal | abctools | Examples of coalescent data | matrix | 100000 | 9 |
coalobs | abctools | Examples of coalescent data | matrix | 100 | 9 |
binomialdata | bayesCT | Binomial dataset for analyzing adaptive Bayesian trials | data.frame | 300 | 4 |
normaldata | bayesCT | Gaussian dataset for analyzing adaptive Bayesian trials | data.frame | 300 | 4 |
survivaldata | bayesCT | Time-to-event dataset for analyzing adaptive Bayesian trials | data.frame | 100 | 4 |
alumnadoEST | RcmdrPlugin.EACSPIR | Valoracion del alumnado de la asignatura de Estadistica | data.frame | 250 | 28 |
depresion | RcmdrPlugin.EACSPIR | Datos simulados sobre depresion | data.frame | 21 | 2 |
evalBurnout | RcmdrPlugin.EACSPIR | Evaluacion del Burnout en personal de enfermeria | data.frame | 62 | 55 |
fobia | RcmdrPlugin.EACSPIR | Eficacia tratamiento para la fobia | data.frame | 160 | 15 |
hoteles | RcmdrPlugin.EACSPIR | Valoracion del grado de satisfaccion de los clientes de hoteles | data.frame | 83 | 23 |
memoriaVisual | RcmdrPlugin.EACSPIR | Memoria visual en una muestra de pacientes fobicos | data.frame | 30 | 3 |
prevencionRL | RcmdrPlugin.EACSPIR | Conducta Prevencionista Responsable | data.frame | 65 | 25 |
riesgosPS | RcmdrPlugin.EACSPIR | Valoracion de riesgos psicosociales en la empresa | data.frame | 990 | 13 |
testBarcelona | RcmdrPlugin.EACSPIR | Datos del test Barcelona | data.frame | 499 | 25 |
s01 | densityarea | Vowel Space Data | tbl_df | 4245 | 10 |
sii_levelmax_sf16_993 | ggsolvencyii | sii_levelmax_sf16_993 | tbl_df | 8 | 2 |
sii_levelmax_sf16_995 | ggsolvencyii | sii_levelmax_sf16_995 | tbl_df | 8 | 2 |
sii_plotdetails_sf16 | ggsolvencyii | sii_plotdetails_sf16 | data.frame | 20 | 8 |
sii_structure_sf16_eng | ggsolvencyii | sii_structure_sf16_eng | tbl_df | 43 | 3 |
sii_structure_sf16_nld | ggsolvencyii | sii_structure_sf16_nld | tbl_df | 43 | 3 |
sii_x_edgecolors_sf16_eng | ggsolvencyii | sii_x_edgecolors_sf16_eng | character | | |
sii_x_edgecolors_sf16_nld | ggsolvencyii | sii_x_edgecolors_sf16_nld | character | | |
sii_x_fillcolors_sf16_eng | ggsolvencyii | sii_x_fillcolors_sf16_eng | character | | |
sii_x_fillcolors_sf16_nld | ggsolvencyii | sii_x_fillcolors_sf16_nld | character | | |
sii_z_ex1_data | ggsolvencyii | sii_z_ex1_data | data.frame | 230 | 6 |
sii_z_ex1_edgecolors | ggsolvencyii | sii_z_ex1_edgecolors | character | | |
sii_z_ex1_fillcolors | ggsolvencyii | sii_z_ex1_fillcolors | character | | |
sii_z_ex1_levelmax | ggsolvencyii | sii_z_ex1_levelmax | data.frame | 5 | 2 |
sii_z_ex1_plotdetails | ggsolvencyii | sii_z_ex1_plotdetails #' A table for 'geom_sii_risksurface' and 'geom_sii_riskoutline' indicating which outlines of each item should be shown, specified per level and/or description. the latter overrule the former. when defining an item (or the 'squared = TRUE' transformation) 4 lines can be distinguished, a radialline going outwards, a circle segment (clockwise), a radialline going inwards, a circle segment (counterclockwise). These are numbered as outline1 to outline4. | data.frame | 13 | 8 |
sii_z_ex1_plotdetails2 | ggsolvencyii | sii_z_ex1_plotdetails2 #' A table for 'geom_sii_risksurface' and 'geom_sii_riskoutline' indicating which outlines of each item should be shown, specified per level and/or description. the latter overrule the former. when defining an item (or the 'squared = TRUE' transformation) 4 lines can be distinguished, a radialline going outwards, a circle segment (clockwise), a radialline going inwards, a circle segment (counterclockwise). These are numbered as outline1 to outline4. | data.frame | 13 | 8 |
sii_z_ex1_structure | ggsolvencyii | sii_z_ex1_structure | tbl_df | 25 | 3 |
sii_z_ex2_data | ggsolvencyii | sii_z_ex2_data | data.frame | 23 | 5 |
sii_z_ex3_data | ggsolvencyii | sii_z_ex3_data | data.frame | 129 | 6 |
sii_z_ex3_plotdetails | ggsolvencyii | sii_z_ex3_plotdetails #' A table for 'geom_sii_risksurface' and 'geom_sii_riskoutline' indicating which outlines of each item should be shown, specified per level and/or description. the latter overrule the former. when defining an item (or the 'squared = TRUE' transformation) 4 lines can be distinguished, a radialline going outwards, a circle segment (clockwise), a radialline going inwards, a circle segment (counterclockwise). These are numbered as outline1 to outline4. | data.frame | 24 | 8 |
sii_z_ex4_data | ggsolvencyii | sii_z_ex4_data | data.frame | 27 | 6 |
sii_z_ex4_levelmax | ggsolvencyii | sii_z_ex4_levelmax | data.frame | 3 | 2 |
sii_z_ex4_structure | ggsolvencyii | sii_z_ex4_structure | tbl_df | 11 | 3 |
sii_z_ex6_data | ggsolvencyii | sii_z_ex6_data | data.frame | 49 | 6 |
sii_z_ex6_data2 | ggsolvencyii | sii_z_ex6_data2 | data.frame | 49 | 6 |
sii_z_ex6_edgecolors | ggsolvencyii | sii_z_ex6_edgecolors | character | | |
sii_z_ex6_fillcolors | ggsolvencyii | sii_z_ex6_fillcolors | character | | |
sii_z_ex6_levelmax | ggsolvencyii | sii_z_ex6_levelmax | data.frame | 12 | 2 |
sii_z_ex6_plotdetails | ggsolvencyii | sii_z_ex6_plotdetails #' A table for 'geom_sii_risksurface' and 'geom_sii_riskoutline' indicating which outlines of each item should be shown, specified per level and/or description. the latter overrule the former. when defining an item (or the 'squared = TRUE' transformation) 4 lines can be distinguished, a radialline going outwards, a circle segment (clockwise), a radialline going inwards, a circle segment (counterclockwise). These are numbered as outline1 to outline4. | data.frame | 12 | 8 |
sii_z_ex6_structure | ggsolvencyii | sii_z_ex6_structure | tbl_df | 49 | 3 |
sii_z_ex7_data | ggsolvencyii | sii_z_ex7_data | data.frame | 86 | 6 |
sii_z_ex7_plotdetails | ggsolvencyii | sii_z_ex7_plotdetails #' A table for 'geom_sii_risksurface' and 'geom_sii_riskoutline' indicating which outlines of each item should be shown, specified per level and/or description. the latter overrule the former. when defining an item (or the 'squared = TRUE' transformation) 4 lines can be distinguished, a radialline going outwards, a circle segment (clockwise), a radialline going inwards, a circle segment (counterclockwise). These are numbered as outline1 to outline4. | data.frame | 22 | 8 |
shen_orr_ex | dtangle | Example Subset of Shen-Orr deconvolution data set. | list | | |
bdparData | bdpar | Example of the content of the files to be preprocessed. | data.frame | 40 | 2 |
emojisData | bdpar | Emojis codes and descriptions data. | tbl_df | 2623 | 2 |
beta_mdat | detectnorm | Example meta-analysis: Extremely Non-normal Data | data.frame | 40 | 13 |
trun_mdat | detectnorm | Example meta-analysis: Truncated Normal Data | data.frame | 40 | 13 |
TwentyNewsgroups | LDAvis | Twenty Newsgroups Data | list | | |
connectivity_network | conserveR | connectivity_network A bipartite network of methods included in the conserveR package linked by shared cited references. Used for visualization in 'map_selection' | network | | |
edge | conserveR | edge An example dataset of the output of 'find_method'. Conservation prioritization methods prioritized by fit to an example set of data requirements. | data.frame | 134 | 9 |
literature | conserveR | Literature | tbl_df | 134 | 43 |
mca_results | conserveR | mca_results | tbl_df | 134 | 7 |
traits | conserveR | Traits | tbl_df | 134 | 32 |
goghColors | ggRtsy | Sampling of Colors from Van Gogh Paintings | tbl_df | 986 | 3 |
goghPaintingSets | ggRtsy | Van Gogh Paintings Information | tbl_df | 1931 | 6 |
abundances | yatah | Abundance table for 199 samples. | data.frame | 1585 | 200 |
all_ranks | yatah | Ranks handled by 'yatah' | character | | |
lebedev | DirStats | Lebedev quadrature on the sphere | data.frame | 5810 | 2 |
x3p4c | odetector | Synthetic data set consists of three variables with four clusters | matrix | 130 | 4 |
star | evalITR | Tennesseeโs Student/Teacher Achievement Ratio (STAR) project | data.frame | 1911 | 14 |
credit_data | SWIM | Credit data set | matrix | 100000 | 7 |
biomedicalrevenue | ggcharts | Top Biomedical Companies Revenues | data.frame | 224 | 3 |
popch | ggcharts | Population Statistics of Switzerland | data.frame | 42 | 3 |
popeurope | ggcharts | European Population | data.frame | 30 | 3 |
revenue_wide | ggcharts | Top Biomedical Companies Revenues | tbl_df | 8 | 29 |
beer | windows.pls | Beer Dataset from Near Infrared Spectroscopy | data.frame | 80 | 577 |
us_fertilizer_county | usfertilizer | us_fertilizer_county | tbl_df | 625580 | 12 |
noAxiom | revealedPrefs | revealedPrefs example datasets | list | | |
noGarp | revealedPrefs | revealedPrefs example datasets | list | | |
noSarp | revealedPrefs | revealedPrefs example datasets | list | | |
noWarp | revealedPrefs | revealedPrefs example datasets | list | | |
okSarp | revealedPrefs | revealedPrefs example datasets | list | | |
book.tee.data | mrds | Golf tee data used in chapter 6 of Advanced Distance Sampling examples | list | | |
lfbcvi | mrds | Black-capped vireo mark-recapture distance sampling analysis | data.frame | 2506 | 13 |
lfgcwa | mrds | Golden-cheeked warbler mark-recapture distance sampling analysis | data.frame | 2430 | 13 |
pronghorn | mrds | Pronghorn aerial survey data from Wyoming | data.frame | 660 | 5 |
ptdata.distance | mrds | Single observer point count data example from Distance | data.frame | 144 | 6 |
ptdata.dual | mrds | Simulated dual observer point count data | data.frame | 420 | 6 |
ptdata.removal | mrds | Simulated removal observer point count data | data.frame | 408 | 6 |
ptdata.single | mrds | Simulated single observer point count data | data.frame | 341 | 4 |
stake77 | mrds | Wooden stake data from 1977 survey | data.frame | 150 | 10 |
stake78 | mrds | Wooden stake data from 1978 survey | data.frame | 150 | 13 |
Fishing | gofcat | Choice of Fishing Mode | data.frame | 1182 | 10 |
retinopathy | gofcat | Retinopathy | data.frame | 613 | 5 |
vaso | gofcat | Vasoconstriction and Breathing | data.frame | 39 | 3 |
alcohol_crc | dosresmeta | Eight published studies on the relation between alcohol intake and colorectal cancer | data.frame | 48 | 7 |
alcohol_cvd | dosresmeta | Six published studies on the relation between alcohol intake and cardiovascular disease risk | data.frame | 25 | 8 |
alcohol_esoph | dosresmeta | Fourteen case-control studies on the relation between alcohol consumption and esophageal cancer | data.frame | 63 | 10 |
alcohol_lc | dosresmeta | Four published studies on the relation between alcohol intake and lung cancer | data.frame | 20 | 7 |
ari | dosresmeta | Five clinical trials on the relation between aripiprazole and schizophrenia | data.frame | 18 | 6 |
bmi_rc | dosresmeta | Four case-control studies on the relation between Body Mass Index and renal cell cancer | data.frame | 33 | 13 |
cc_ex | dosresmeta | Case-control data on alcohol and breast cancer risk | data.frame | 4 | 10 |
ci_ex | dosresmeta | Cumulative incidence data on high-fat dairy food and colorectal cancer risk | data.frame | 5 | 8 |
coffee_cancer | dosresmeta | Eight prospective studies on the relation between coffee consumption and cancer mortality | data.frame | 59 | 9 |
coffee_cvd | dosresmeta | Thirteen prospective studies on the relation between coffee consumption and cardiovascular mortality | data.frame | 92 | 12 |
coffee_mort | dosresmeta | Twenty-one prospective studies on the relation between coffee consumption and all-cause mortality | data.frame | 101 | 11 |
coffee_mort_add | dosresmeta | Additional two prospective studies on the relation between coffee consumption and all-cause mortality | data.frame | 29 | 11 |
coffee_stroke | dosresmeta | Eleven prospective studies on the relation between coffee consumption and stroke risk | data.frame | 68 | 12 |
fish_ra | dosresmeta | Six studies on the relation between fish consumption and rheumatoid arthritis risk | data.frame | 22 | 12 |
ir_ex | dosresmeta | Incidence-rate data on fiber intake and coronary heart disease risk | data.frame | 5 | 8 |
milk_mort | dosresmeta | Eleven prospective studies on the relation between milk consumption and all-cause mortality | data.frame | 56 | 12 |
milk_ov | dosresmeta | Nine studies on the relation between milk consumption and ovarian cancer | data.frame | 37 | 12 |
oc_breast | dosresmeta | Twenty-two case-control studies on the relation between oral contraceptives use and breast cancer | data.frame | 113 | 14 |
process_bc | dosresmeta | Ten studies on the relation between processed meat and bladder cancer | data.frame | 46 | 15 |
red_bc | dosresmeta | Twelve studies on the relation between red meat and bladder cancer | data.frame | 51 | 15 |
sim_os | dosresmeta | Simulated data for one-stage dose-response meta-analysis | data.frame | 27 | 11 |
big5 | frequency | Big 5 Personality Factors Survey Data | data.frame | 15735 | 56 |
xymap | PROJ | xymap data for testing | matrix | 5494 | 2 |
Tourism | wINEQ | Sample survey on trips | tbl_df | 5319 | 17 |
Well_being | wINEQ | Sample survey on quality of life | tbl_df | 1197 | 27 |
alignment_vals | ggalignment | Alignment Values | data.frame | 9 | 1 |
heart_disease | cheese | Heart Disease | tbl_df | 303 | 9 |
bin_ranges | checkLuhn | BIN ranges | tbl_df | 48 | 5 |
ipfpwap | ipft | Indoor localization data set with the positions of the wireless access points present in the ipftrain and ipftest data sets. Unknown locations are stored as NAs. Data from the positioning tutorial of the seventh international conference on indoor Positioning and Indoor Navigation (IPIN2016). | data.frame | 168 | 2 |
ipftest | ipft | Indoor localization test data set to test Indoor Positioning System that rely on WLAN/WiFifingerprint. It was created during the Fingerprinting-based Indoor Positioning tutorial of the seventh international conference on indoor Positioning and Indoor Navigation (IPIN2016). | data.frame | 702 | 176 |
ipftrain | ipft | Indoor localization training data set to test Indoor Positioning System that rely on WLAN/WiFifingerprint. It was created during the Fingerprinting-based Indoor Positioning tutorial of the seventh international conference on indoor Positioning and Indoor Navigation (IPIN2016). | data.frame | 927 | 176 |
df_hospitals_ortho | mactivate | Orthopedic Device Sales | data.frame | 4703 | 15 |
Dickinson_design | cvcrand | Raw county-level variables for study 1 in Dickinson et al (2015) | data.frame | 16 | 11 |
Dickinson_outcome | cvcrand | Simulated individual-level binary outcome and baseline variables for study 1 in Dickinson et al (2015) | data.frame | 4800 | 7 |
breastcancer | OneR | Breast Cancer Wisconsin Original Data Set | data.frame | 699 | 10 |
coral6 | lablaster | Time resolved analysis by laser ablation inductively coupled plasma mass spectrometry of a branching coral, identified hereon as โcoral6โ. | data.frame | 300 | 5 |
foram166shot7 | lablaster | Time resolved analysis by laser ablation inductively coupled plasma mass spectrometry of a planktonic foraminifera | data.frame | 144 | 8 |
foram174shot4 | lablaster | Time resolved analysis by laser ablation inductively coupled plasma mass spectrometry of a planktonic foraminifera | data.frame | 144 | 8 |
foram72shot3 | lablaster | Time resolved analysis by laser ablation inductively coupled plasma mass spectrometry of a planktonic foraminifera | data.frame | 144 | 8 |
C1 | nlreg | Six Herbicide Data Sets | data.frame | 42 | 3 |
C2 | nlreg | Six Herbicide Data Sets | data.frame | 49 | 3 |
C3 | nlreg | Six Herbicide Data Sets | data.frame | 51 | 3 |
C4 | nlreg | Six Herbicide Data Sets | data.frame | 50 | 3 |
M2 | nlreg | Six Herbicide Data Sets | data.frame | 40 | 3 |
M4 | nlreg | Six Herbicide Data Sets | data.frame | 72 | 3 |
chlorsulfuron | nlreg | Chlorsulfuron Data | data.frame | 51 | 3 |
daphnia | nlreg | 'Daphnia Magna' Data | data.frame | 136 | 2 |
helicopter | nlreg | Helicopter Data | data.frame | 9 | 6 |
metsulfuron | nlreg | Metsulfuron Methyl Data | data.frame | 40 | 3 |
ria | nlreg | Radioimmunoassay Data | data.frame | 16 | 2 |
ttrc | TTR | Technical Trading Rule Composite data | data.frame | 5550 | 6 |
aids | cond | AIDS Symptoms and AZT Use Data | data.frame | 4 | 4 |
airway | cond | Airway Data | data.frame | 35 | 6 |
babies | cond | Crying Babies Data | data.frame | 36 | 4 |
dormicum | cond | Dormicum Data | data.frame | 37 | 3 |
fraudulent | cond | Fraudulent Automobile Insurance Claims Data | data.frame | 42 | 12 |
fungal | cond | Fungal Infections Treatment Data | data.frame | 10 | 4 |
rabbits | cond | Rabbits Data | data.frame | 10 | 4 |
urine | cond | Urine Data | data.frame | 77 | 7 |
coronavirus | coronavirus | The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset | data.frame | 973836 | 15 |
covid19_vaccine | coronavirus | The COVID-19 Worldwide Vaccine Dataset | data.frame | 142597 | 15 |
ILE | ClusTorus | ILE: Structure of the Isoleucine | data.frame | 8080 | 4 |
SARS_CoV_2 | ClusTorus | SARS-CoV-2: chain B of Structure of the SARS-CoV-2 spike glycoprotein(closed state) | data.frame | 972 | 2 |
data_6VXX | ClusTorus | 6VXX: Structure of the SARS-CoV-2 spike glycoprotein(closed state) | list | | |
toydata1 | ClusTorus | toydata1: Labelled Data for 5 Clusters | data.frame | 540 | 3 |
toydata2 | ClusTorus | toydata2: Labelled Data for 3 Clusters | data.frame | 1000 | 3 |
King200Breast | SwimmeR | Results for Lilly King's 200 Breaststrokes | spec_tbl_df | 50 | 4 |
state_boundaries_wgs84 | USA.state.boundaries | state_boundaries_wgs84 with sf read data | sf | 61 | 14 |
dat.metap | metap | Example data | list | | |
CD002943_CMP001 | metarep | Data in meta-analysis reported in review CD002943, 'Cochrane library'. | data.frame | 5 | 12 |
CD003366_CMP005 | metarep | Data in meta-analysis reported in review CD003366, 'Cochrane library'. | data.frame | 28 | 12 |
CD006823_CMP001 | metarep | Data in meta-analysis reported in review CD006823, 'Cochrane library'. | data.frame | 7 | 12 |
CD007077_CMP001 | metarep | Data in meta-analysis reported in review CD007077, 'Cochrane library'. | data.frame | 5 | 12 |
MetsaKasvVyoh | efdm | Finnish bio-geographical regions | sf | 298 | 2 |
example | efdm | Example dataset. | list | | |
CFAdata | CFAcoop | Colony Formation Assay data on cellular cooperation | data.frame | 454 | 8 |
ICAapp | ccmEstimator | Application data | data.frame | 1602 | 14 |
VSGFS | DoE.base | VSGFS: an experiment using an optimized orthogonal array in 72 runs | design | 72 | 10 |
riskcor | SEset | Cognitive risk sample correlation matrix | matrix | 6 | 6 |
amphibians | AtlasMaker | amphibians | SpatialPolygonsDataFrame | | |
birds | AtlasMaker | birds | SpatialPolygonsDataFrame | | |
counties_NY | AtlasMaker | counties_NY | sf | 62 | 7 |
flowering_plants | AtlasMaker | flowering_plants | SpatialPolygonsDataFrame | | |
points | AtlasMaker | points | function | | |
points_campgrounds | AtlasMaker | points_campgrounds | tbl_df | 116 | 3 |
points_parks | AtlasMaker | points_parks | tbl_df | 254 | 3 |
points_watchsites | AtlasMaker | points_watchsites | tbl_df | 76 | 3 |
reptiles | AtlasMaker | reptiles | SpatialPolygonsDataFrame | | |
roads_ny_interstate | AtlasMaker | roads_ny_interstate | sf | 245 | 5 |
unemp | mFilter | US Quarterly Unemployment Series | ts | | |
brexit | texter | This is the first data to be included in my package | data.frame | 100 | 2 |
doge | texter | This is the first data to be included in my package | data.frame | 1000 | 3 |
nrc | texter | This data was saved NRC word-emotion association lexicon | data.frame | 13901 | 4 |
stop_words | texter | Saved stop_word dataframe from tidytext | tbl_df | 1149 | 2 |
iBAQ | CoFRA | data frame containing iBAQ values | data.frame | 18889 | 33 |
coords | sgstar | Coordinate of region in South Sumatera | matrix | 17 | 2 |
simulatedata | sgstar | Sample Data for simulate analysis data | data.frame | 100 | 17 |
indonRespir | gammSlice | Eespiratory infection in Indonesian children | data.frame | 1200 | 12 |
toenail | gammSlice | Toenail infection clinical trial | data.frame | 1908 | 5 |
CGM.Cat | bionetdata | Cancer Gene Modules | data.frame | 2033 | 10 |
DD.chem.data | bionetdata | Drug-drug chemical similarities data | matrix | 1253 | 1253 |
DrugBank.Cat | bionetdata | DrugBank categories | matrix | 1253 | 45 |
FIN.data | bionetdata | Functional Interaction Network data for human. | data.frame | 2033 | 2033 |
Yeast.Biogrid.FunCat | bionetdata | Yeast FunCat classes for 'BioGRID' data. | data.frame | 4531 | 233 |
Yeast.Biogrid.data | bionetdata | Yeast BioGRID data | matrix | 4531 | 4531 |
Yeast.STRING.FunCat | bionetdata | Yeast FunCat classes for 'STRING' data. | data.frame | 2338 | 177 |
Yeast.STRING.data | bionetdata | Yeast interactions from STRING | matrix | 2338 | 2338 |
trim32 | abess | The Bardet-Biedl syndrome Gene expression data | data.frame | 120 | 501 |
HMDB_blood | AlpsNMR | The Human Metabolome DataBase multiplet table: blood metabolites normally found in NMR-based metabolomics | data.frame | 224 | 8 |
HMDB_cell | AlpsNMR | The Human Metabolome DataBase multiplet table: cell metabolites normally found in NMR-based metabolomics | data.frame | 232 | 6 |
HMDB_urine | AlpsNMR | The Human Metabolome DataBase multiplet table: urine metabolites normally found in NMR-based metabolomics | data.frame | 1266 | 9 |
Parameters_blood | AlpsNMR | to rDolphin | data.frame | 14 | 2 |
Parameters_cell | AlpsNMR | Parameters for cell samples profiling | data.frame | 14 | 2 |
Parameters_urine | AlpsNMR | Parameters for urine samples profiling | data.frame | 14 | 2 |
ROI_blood | AlpsNMR | ROIs for blood (plasma/serum) samples | data.frame | 35 | 12 |
ROI_cell | AlpsNMR | ROIs for cell samples | data.frame | 44 | 12 |
ROI_urine | AlpsNMR | ROIs for urine samples | data.frame | 59 | 12 |
hmdb | AlpsNMR | The Human Metabolome DataBase multiplet table | tbl_df | 2629 | 12 |
mtx | zitools | Matrix Data | matrix | 100 | |
resultsIris | igate | Example results data file to be used for example report generation. | data.frame | 2 | 13 |
validatedObsIris | igate | validatedObsIris data set | data.frame | 31 | 4 |
validationCountsIris | igate | validationCountsIris data set | data.frame | 2 | 3 |
validationSummaryIris | igate | validationSummaryIris data set | tbl_df | 2 | 3 |
NLSYlong | LMest | National Longitudinal Survey of Youth data | data.frame | 1743 | 12 |
PSIDlong | LMest | Dataset about income dynamics | data.frame | 10122 | 13 |
RLMSdat | LMest | Dataset about job satisfaction | data.frame | 1718 | 7 |
RLMSlong | LMest | Dataset about job satisfaction | data.frame | 12026 | 4 |
data_SRHS_long | LMest | Self-reported health status dataset | data.frame | 56592 | 7 |
data_criminal_sim | LMest | Criminal dataset | matrix | 60000 | 13 |
data_drug | LMest | Dataset about marijuana consumption | data.frame | 51 | 6 |
data_employment_sim | LMest | Employment dataset | data.frame | 1755 | 6 |
data_heart_sim | LMest | Health dataset | data.frame | 750 | 8 |
data_long_cont | LMest | Multivariate Longitudinal Continuous (Gaussian) Data | data.frame | 2500 | 7 |
data_market_sim | LMest | Marketing dataset | data.frame | 1000 | 6 |
coffee | ViSiElse | Simulated time data of the coffee process | data.frame | 10 | 6 |
intubation | ViSiElse | Intubation time data from a simulation of a neonatal resuscitation | data.frame | 37 | 7 |
shoppingBehavior | ViSiElse | Simulated online shopping behavior time data | data.frame | 100 | 7 |
typDay | ViSiElse | Simulated time data of the actions performed in a typical day | data.frame | 100 | 15 |
FCWB.demo | nat.templatebrains | Sample template brain: FlyCircuit Whole Brain | templatebrain | | |
pedigree | SeqVarTools | Pedigree for example data | data.frame | 90 | 6 |
election2018Cities | covid19br | Results of the 2018 presidential election in Brazil by city. | tbl_df | 5570 | 11 |
election2018Regions | covid19br | Results of the 2018 presidential election in Brazil by region. | tbl_df | 5 | 4 |
election2018States | covid19br | Results of the 2018 presidential election in Brazil by state. | grouped_df | 27 | 5 |
UKgrid | UKgrid | The UK National Electricity Transmission System Dataset | data.frame | 254592 | 9 |
APAP | pksensi | Pharmacokinetic Dataset of Acetaminophen | data.frame | 32 | 7 |
dtClimate | ggTimeSeries | Climate data. | data.table | 23628 | 5 |
RSdata | sensmediation | Example data for the functions in sensmediation | data.frame | 1000 | 5 |
ibex_hr | boxfilter | One year of heart rates of a capricorn free-living in the alps. | data.frame | 28454 | 2 |
sleepduration | boxfilter | | data.frame | 881 | 2 |
wb_month | boxfilter | One month of heart rates and their quality in a wild boar. Quality was assessed by Star-Oddi, Island. | data.frame | 3720 | 3 |
wb_year | boxfilter | One year of heart rates of a wild boar female. | data.frame | 54719 | 2 |
karate | einet | Zachary's karate club | igraph | | |
Y | NBtsVarSel | Observation matrix Y | numeric | | |
siccodes | finreportr | Standard Industrial Classification Code List | data.frame | 444 | 2 |
statecodes | finreportr | EDGAR State and Country Codes | data.frame | 310 | 2 |
data.sim | CRTgeeDR | The data.sim Dataset. | data.frame | 10000 | 11 |
data.adjacent.mat | AST | data frame of adjacent provinces in Iran | matrix | 31 | |
data.residual.AST | AST | residual data set | data.frame | 3000 | 6 |
brate | minque | Cotton boll retention rate data | data.frame | 338 | 5 |
cot | minque | Twenty four cotton genotypes with four agronomic traits | data.frame | 288 | 7 |
maize | minque | Maize variety trial | data.frame | 260 | 4 |
ncii | minque | NC design II F1 data | data.frame | 60 | 4 |
cereb | BCgee | Cerebrovascular Deficiency | data.frame | 134 | 4 |
seizure | BCgee | Epiliptic Seizures | data.frame | 59 | 7 |
star | BET | Coordinates of Brightest Stars in the Night Sky | data.frame | 256 | 2 |
cmip6 | quadmesh | CMIP6 sample | RasterBrick | | |
etopo | quadmesh | World topography map | RasterLayer | | |
worldll | quadmesh | World raster map | RasterLayer | | |
xymap | quadmesh | World map | matrix | 82403 | 2 |
economo | ggsegEconomo | economo atlas | brain_atlas | | |
economo_3d | ggsegEconomo | economo atlas | ggseg3d_atlas | 4 | 4 |
Etna_boundary | movecost | Dataset: bounding polygon representing a study area on Mount Etna (Sicily, Italy) | SpatialPolygonsDataFrame | | |
Etna_end_location | movecost | Dataset: locations on Mount Etna (Sicily, Italy) | SpatialPointsDataFrame | | |
Etna_start_location | movecost | Dataset: location on Mount Etna (Sicily, Italy) | SpatialPointsDataFrame | | |
destin.loc | movecost | Dataset: locations on the volcano Maunga Whau (Auckland, New Zealand) | SpatialPointsDataFrame | | |
malta_dtm_40 | movecost | Dataset: Malta DTM (40m cell size) | RasterLayer | | |
springs | movecost | Dataset: location of springs in Malta | SpatialPointsDataFrame | | |
volc | movecost | Dataset: raster dataset representing the elevation of the volcano Maunga Whau (Auckland, New Zealand) | RasterLayer | | |
volc.loc | movecost | Dataset: location on the volcano Maunga Whau (Auckland, New Zealand) | SpatialPointsDataFrame | | |
associations_ex01 | gwasrapidd | gwasrapidd entities' examples | associations | | |
associations_ex02 | gwasrapidd | gwasrapidd entities' examples | associations | | |
cytogenetic_bands | gwasrapidd | GRCh38 human cytogenetic bands. | tbl_df | 862 | 8 |
studies_ex01 | gwasrapidd | gwasrapidd entities' examples | studies | | |
studies_ex02 | gwasrapidd | gwasrapidd entities' examples | studies | | |
traits_ex01 | gwasrapidd | gwasrapidd entities' examples | traits | | |
traits_ex02 | gwasrapidd | gwasrapidd entities' examples | traits | | |
variants_ex01 | gwasrapidd | gwasrapidd entities' examples | variants | | |
variants_ex02 | gwasrapidd | gwasrapidd entities' examples | variants | | |
Data_saekernel | saekernel | Sample Data for Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel | data.frame | 100 | 3 |
ewbabynames | ukbabynames | England & Wales baby names | tbl_df | 294801 | 6 |
nibabynames | ukbabynames | Northern Ireland baby names | tbl_df | 22596 | 6 |
rankings | ukbabynames | England & Wales top-100 baby names by year | tbl_df | 1900 | 4 |
scotbabynames | ukbabynames | Scotland baby names | tbl_df | 248420 | 6 |
ukbabynames | ukbabynames | UK baby names | tbl_df | 565817 | 6 |
a10 | fpp2 | Monthly anti-diabetic drug subsidy in Australia from 1991 to 2008. | ts | | |
arrivals | fpp2 | International Arrivals to Australia | mts | 127 | 4 |
ausair | fpp2 | Air Transport Passengers Australia | ts | | |
ausbeer | fpp2 | Quarterly Australian Beer production | ts | | |
auscafe | fpp2 | Monthly expenditure on eating out in Australia | ts | | |
austa | fpp2 | International visitors to Australia | ts | | |
austourists | fpp2 | International Tourists to Australia: Total visitor nights. | ts | | |
calls | fpp2 | Call volume for a large North American bank | msts | | |
debitcards | fpp2 | Retail debit card usage in Iceland. | ts | | |
departures | fpp2 | Total monthly departures from Australia | mts | 498 | 5 |
elecdaily | fpp2 | Half-hourly and daily electricity demand for Victoria, Australia, in 2014 | mts | 365 | 3 |
elecdemand | fpp2 | Half-hourly and daily electricity demand for Victoria, Australia, in 2014 | msts | 17520 | 3 |
elecequip | fpp2 | Electrical equipment manufactured in the Euro area. | ts | | |
elecsales | fpp2 | Electricity sales to residential customers in South Australia. | ts | | |
euretail | fpp2 | Quarterly retail trade: Euro area. | ts | | |
gasoline | fpp2 | US finished motor gasoline product supplied. | ts | | |
goog | fpp2 | Daily closing stock prices of Google Inc | ts | | |
goog200 | fpp2 | Daily closing stock prices of Google Inc | ts | | |
guinearice | fpp2 | Rice production (Guinea) | ts | | |
h02 | fpp2 | Monthly corticosteroid drug subsidy in Australia from 1991 to 2008. | ts | | |
hyndsight | fpp2 | Daily pageviews for the Hyndsight blog. 30 April 2014 to 29 April 2015. | ts | | |
insurance | fpp2 | Insurance quotations and advertising expenditure. | mts | 40 | 2 |
livestock | fpp2 | Livestock (sheep) in Asia, 1961-2007. | ts | | |
marathon | fpp2 | Boston marathon winning times since 1897 | ts | | |
maxtemp | fpp2 | Maximum annual temperatures at Moorabbin Airport, Melbourne | ts | | |
melsyd | fpp2 | Total weekly air passenger numbers on Ansett airline flights between Melbourne and Sydney, 1987-1992. | mts | 283 | 3 |
mens400 | fpp2 | Winning times in Olympic men's 400m track final. 1896-2016. | ts | | |
oil | fpp2 | Annual oil production in Saudi Arabia | ts | | |
prison | fpp2 | prison | mts | 48 | 32 |
prisonLF | fpp2 | prison | tbl_df | 1536 | 5 |
qauselec | fpp2 | Quarterly Australian Electricity production | ts | | |
qcement | fpp2 | Quarterly Australian Portland Cement production | ts | | |
qgas | fpp2 | Quarterly Australian Gas Production | ts | | |
sunspotarea | fpp2 | Annual average sunspot area (1875-2015) | ts | | |
uschange | fpp2 | Growth rates of personal consumption and personal income in the USA. | mts | 187 | 5 |
usmelec | fpp2 | Electricity monthly total net generation. January 1973 - June 2013. | ts | | |
visnights | fpp2 | Quarterly visitor nights for various regions of Australia. | mts | 76 | 20 |
wmurders | fpp2 | Annual female murder rate (per 100,000 standard population) in the USA. 1950-2004. | ts | | |
church | SparseVFC | The Church Photos | list | | |
BulkFlu | scBio | Gene expression profiles of flu and pbs sample. | data.frame | 1858 | 74 |
SCCellSpace | scBio | Single-cell cell space. | matrix | 349 | 2 |
SCFlu | scBio | Gene expression profiles of lung cells after influenza infection. | data.frame | 1858 | 349 |
SCLabels | scBio | Single-cell classification into cell types. | character | | |
US.df | ar.matrix | Spatial Polygons Data Frame of Counties for Several States | SpatialPolygonsDataFrame | | |
US.graph | ar.matrix | Matrix of Shared Boundaries Between US.df Counties | matrix | 475 | 475 |
pixar_films | headliner | This data comes from 'pixarfilms' package by Eric Leung (2022) | tbl_df | 22 | 10 |
pain | DBR | Pain Data | data.frame | 1318 | 3 |
KC_Perennial_Vegetables | FAO56 | Crop Coefficients (Kc) of Perennial Vegetables | data.frame | 4 | 4 |
Kc_Cereals | FAO56 | Crop Coefficients (Kc) of Cereals | data.frame | 17 | 4 |
Kc_Fibre_Crops | FAO56 | Crop Coefficients (Kc) of Fibre Crops | data.frame | 3 | 4 |
Kc_Forages | FAO56 | Crop Coefficients (Kc) of Forages | data.frame | 15 | 4 |
Kc_Fruit_Trees | FAO56 | Crop Coefficients (Kc) of Fruit Trees | data.frame | 21 | 4 |
Kc_Grapes_and_Berries | FAO56 | Crop Coefficients (Kc) of Grapes and Berries | data.frame | 4 | 4 |
Kc_Legumes | FAO56 | Crop Coefficients (Kc) of Legumes | data.frame | 13 | 4 |
Kc_Oil_Crops | FAO56 | Crop Coefficients (Kc) of Oil Crops | data.frame | 8 | 4 |
Kc_Roots_and_Tubers | FAO56 | Crop Coefficients (Kc) of Roots and Tubers | data.frame | 8 | 4 |
Kc_Small_Vegetables | FAO56 | Crop Coefficients (Kc) of Small Vegetables | data.frame | 13 | 4 |
Kc_Special | FAO56 | Crop Coefficients (Kc) of Special Areas | data.frame | 2 | 4 |
Kc_Sugar_Cane | FAO56 | Crop Coefficients (Kc) of Sugar Cane | data.frame | 1 | 4 |
Kc_Tropical_Fruits_and_Trees | FAO56 | Crop Coefficients (Kc) of Tropical Fruits and Trees | data.frame | 12 | 4 |
Kc_Vegetables_Cucumber_Family | FAO56 | Crop Coefficients (Kc) of Cucumber Family Vegetables | data.frame | 7 | 4 |
Kc_Vegetables_Solanum_Family | FAO56 | Crop Coefficients (Kc) of Solanum Family Vegetables | data.frame | 4 | 4 |
Kc_Wetlands_Temperate_Climate | FAO56 | Crop Coefficients (Kc) of Wetlands Temperate Climate | data.frame | 5 | 4 |
painbow_data | painbow | A 2D heatmap from XKCD's painbow comic | tbl_df | 58425 | 3 |
QuadRules | mvQuad | nodes and weights for 1D - Gauss-Quadrature | list | | |
topcolour.ig.vancouver.2014 | ig.vancouver.2014.topcolour | Instagram 2014 Vancouver dataset top colour | data.frame | 245736 | 2 |
testdata | RPscoring | Test Dataset | matrix | 8 | |
caviar_end | onadata | Caviar end data | data.frame | 72 | 3 |
caviar_middle | onadata | Caviar middle data | data.frame | 50 | 3 |
caviar_start | onadata | Caviar start data | data.frame | 26 | 3 |
chinook_customers | onadata | Chinook customer data | data.frame | 59 | 4 |
chinook_employees | onadata | Chinook employee data | data.frame | 8 | 4 |
chinook_invoices | onadata | Chinook invoice data | data.frame | 412 | 2 |
chinook_items | onadata | Chinook item sales data | data.frame | 2240 | 2 |
dolphins | onadata | Bottlenose dolphin social network | data.frame | 159 | 2 |
email_edgelist | onadata | Email edgelist | data.frame | 24929 | 2 |
email_vertices | onadata | Email vertices | data.frame | 1005 | 2 |
eu_referendum | onadata | EU referendum data | data.frame | 382 | 4 |
friends_tv_edgelist | onadata | Friends TV edgelist | data.frame | 2976 | 3 |
g14_edgelist | onadata | G14 edgelist | data.frame | 18 | 3 |
karate | onadata | Zachary's Karate Club edgelist | data.frame | 78 | 2 |
koenigsberg | onadata | Bridges of Koenigsberg edgelist | data.frame | 7 | 2 |
lesmis | onadata | Les Miserables character network | data.frame | 254 | 3 |
londontube_edgelist | onadata | London Tube network edgelist | data.frame | 406 | 4 |
londontube_vertices | onadata | London Tube network vertices | data.frame | 302 | 4 |
madmen_edges | onadata | Mad Men network edgelist | data.frame | 39 | 3 |
madmen_vertices | onadata | Mad Men network vertices | data.frame | 45 | 3 |
netscience | onadata | Network Science collaboration network | data.frame | 2742 | 3 |
ontariopol_edgelist | onadata | Ontario politician Twitter interaction network edglist | data.frame | 6095 | 3 |
ontariopol_vertices | onadata | Ontario politician Twitter interaction network vertices | data.frame | 108 | 4 |
park_reviews | onadata | Yelp park reviews | data.frame | 231 | 4 |
pizza | onadata | Random Acts of Pizza | data.frame | 400 | 5 |
s50_edges | onadata | Teenage Friends and Lifestyle Study network edgelist | data.frame | 122 | 2 |
s50_vertices | onadata | Teenage Friends and Lifestyle Study network vertices | data.frame | 50 | 5 |
schoolfriends_edgelist | onadata | Schoolfriends network edgelist | data.frame | 2105 | 3 |
schoolfriends_vertices | onadata | Schoolfriends network vertices | data.frame | 329 | 3 |
wikivote | onadata | Wikipedia administrator voting network | data.frame | 103688 | 2 |
workfrance_edgelist | onadata | Workplace network edgelist | data.frame | 932 | 3 |
workfrance_vertices | onadata | Workplace network vertices | data.frame | 211 | 2 |
IR_diabetes | icenReg | Interval censored time from diabetes onset to diabetic nephronpathy | data.frame | 731 | 3 |
miceData | icenReg | Lung Tumor Interval Censored Data from Hoel and Walburg 1972 | data.frame | 144 | 3 |
esmdata_preprocessed | esmtools | Preprocessed ESM data set | data.frame | 1200 | 20 |
esmdata_raw | esmtools | Raw ESM data set | data.frame | 1242 | 13 |
esmdata_sim | esmtools | Simulated ESM Data Set | data.frame | 4200 | 18 |
waveDataset1500 | fabMix | Wave dataset | data.frame | 1500 | 22 |
AEdemand | thief | Accident and Emergency demand in the UK | mts | 240 | 13 |
SimData | eyeRead | A simulated dataset with eye tracking data | data.frame | 37 | 10 |
gefcom2012_load | tscompdata | GEFCOM2012 load data | list | | |
gefcom2012_temp | tscompdata | GEFCOM2012 temperature data | list | | |
gefcom2012_wp | tscompdata | GEFCOM2012 wind power data | list | | |
nn3 | tscompdata | NN3 data | list | | |
nn5 | tscompdata | NN5 data | list | | |
nngc1 | tscompdata | NNGC1 data | list | | |
Buli1415 | BTLLasso | Bundesliga Data 2014/15 (Buli1415) | list | | |
Buli1516 | BTLLasso | Bundesliga Data 2015/16 (Buli1516) | list | | |
Buli1617 | BTLLasso | Bundesliga Data 2016/17 (Buli1617) | list | | |
Buli1718 | BTLLasso | Bundesliga Data 2017/18 (Buli1718) | list | | |
BuliResponse | BTLLasso | Bundesliga Data Response Data (BuliResponse) | data.frame | 306 | 4 |
GLES | BTLLasso | German Longitudinal Election Study (GLES) | list | | |
GLESsmall | BTLLasso | Subset of the GLES data set with 200 observations and 4 covariates. | list | | |
SimData | BTLLasso | Simulated data set for illustration | list | | |
lesmis_edges | sigmajs | Edges from co-appearances of characters in "Les Miserables" | data.frame | 1589 | 4 |
lesmis_igraph | sigmajs | Co-appearances of characters in "Les Miserables" as igraph object | igraph | | |
lesmis_nodes | sigmajs | Nodes from co-appearances of characters in "Les Miserables" | data.frame | 181 | 2 |
cleveland | wevid | Example datasets | data.frame | 297 | 3 |
fitonly | wevid | Example datasets | data.frame | 242 | 3 |
pima | wevid | Example datasets | data.frame | 768 | 3 |
almond | biotic | River Almond invertebrate dataset | data.frame | 34 | 6 |
braidburn | biotic | Braid Burn invertebrate dataset | data.frame | 20 | 8 |
greenburn | biotic | Green Burn invertebrate dataset | data.frame | 25 | 8 |
casecohort_data_secondary | ODS | Data example for the secondary analysis in case-cohort design | data.frame | 1000 | 15 |
ods_data | ODS | Data example for analyzing the primary response in ODS design | matrix | 400 | 5 |
ods_data_secondary | ODS | Data example for the secondary analysis in ODS design | matrix | 3000 | 7 |
LeMis | threejs | Les Miserables Character Coappearance Data | igraph | | |
ego | threejs | Facebook social circles | igraph | | |
Conesprings | NetIndices | Cone Spring ecosystem. | matrix | 7 | 6 |
Takapoto | NetIndices | Takapoto atoll planktonic food web | matrix | 8 | 10 |
test | CutpointsOEHR | A simulation data to test cutpointsOEHR | data.frame | 200 | 4 |
batteries | repairData | Batteries | spec_tbl_df | 995 | 12 |
mobiles | repairData | Mobiles | spec_tbl_df | 1916 | 11 |
printers | repairData | Printers | spec_tbl_df | 773 | 12 |
repairs | repairData | Full open repair data dataset | spec_tbl_df | 48669 | 12 |
tablets | repairData | Tablets | spec_tbl_df | 647 | 12 |
beissinger_data | ohtadstats | Chicken Genotype Data | matrix | 1417 | 100 |
miyashita_langley_data | ohtadstats | Drosophila melanogaster genotypes | matrix | 64 | 85 |
annoEtranger | coreNLP | Annotation of first two lines of Albert Camus' L'Etranger | annotation | | |
annoHp | coreNLP | Annotation of first line of JK Rowling's The Philosopher's Stone | annotation | | |
AHCAvote2017 | Stat2Data | Congressional Votes on American Health Care Act (in 2017) | data.frame | 430 | 11 |
AccordPrice | Stat2Data | Prices of Used Honda Accords (in 2017) | data.frame | 30 | 3 |
Airlines | Stat2Data | Ontime Records for Two Airlines at Two Airports | data.frame | 10333 | 5 |
Alfalfa | Stat2Data | Alfalfa Growth | data.frame | 15 | 3 |
AlitoConfirmation | Stat2Data | US Senate Votes on Samuel Alito for the Supreme Court | data.frame | 100 | 6 |
Amyloid | Stat2Data | Amyloid-beta and Cognitive Impairment | data.frame | 57 | 2 |
AppleStock | Stat2Data | Daily Price and Volume of Apple Stock | data.frame | 66 | 4 |
ArcheryData | Stat2Data | Scores in an Archery Class | data.frame | 18 | 7 |
AthleteGrad | Stat2Data | Athletic Participation, Race, and Graduation | data.frame | 214555 | 3 |
AudioVisual | Stat2Data | Reaction Times to Audio and Visual Stimuli | data.frame | 72 | 4 |
AutoPollution | Stat2Data | Noise Levels of Filters to Reduce Automobile Pollution | data.frame | 36 | 4 |
Backpack | Stat2Data | Weights of College Student Backpacks | data.frame | 100 | 9 |
BaseballTimes | Stat2Data | Baseball Game Times of One Day in 2008 | data.frame | 15 | 7 |
BaseballTimes2017 | Stat2Data | Baseball Game Times of One Day in 2017 | data.frame | 14 | 7 |
BeeStings | Stat2Data | Do Bee Stings Depend on Previous Stings? | data.frame | 18 | 3 |
BirdCalcium | Stat2Data | Effect of a Hormone on Bird Calcium Levels | data.frame | 20 | 5 |
BirdNest | Stat2Data | Nest Characteristics for Different Bird Species | data.frame | 84 | 12 |
Blood1 | Stat2Data | Blood Pressure, Weight, and Smoking Status | data.frame | 500 | 3 |
BlueJays | Stat2Data | Blue Jay Measurements | data.frame | 123 | 9 |
BrainpH | Stat2Data | Brain pH Measurements | data.frame | 54 | 5 |
BreesPass | Stat2Data | Drew Brees Passing Statistics (2016) | data.frame | 16 | 5 |
BritishUnions | Stat2Data | Attitudes Towards British Trade Unions | data.frame | 17 | 7 |
ButterfliesBc | Stat2Data | Butterfly (Boloria chariclea) Measurements | data.frame | 32 | 4 |
CAFE | Stat2Data | US Senate Votes on Corporate Average Fuel Economy Bill | data.frame | 100 | 7 |
CO2 | Stat2Data | Daily CO2 Measurements in Germany | data.frame | 237 | 2 |
CO2Germany | Stat2Data | Daily CO2 Measurements in Germany | data.frame | 237 | 2 |
CO2Hawaii | Stat2Data | CO2 Readings in Hawaii | data.frame | 360 | 4 |
CO2SouthPole | Stat2Data | CO2 Readings at the South Pole | data.frame | 348 | 4 |
CalciumBP | Stat2Data | Do Calcium Supplements Lower Blood Pressure? | data.frame | 21 | 2 |
CanadianDrugs | Stat2Data | Canadian Drugs Senate Vote | data.frame | 94 | 6 |
CancerSurvival | Stat2Data | Survival Times for Different Cancers | data.frame | 64 | 2 |
Caterpillars | Stat2Data | Measurements of Manduca Sexta Caterpillars | data.frame | 267 | 18 |
CavsShooting | Stat2Data | Cleveland Cavalier's Shooting (2016-2017) | data.frame | 1940 | 3 |
Cereal | Stat2Data | Nutrition Content of Breakfast Cereals | data.frame | 36 | 4 |
ChemoTHC | Stat2Data | THC for Antinausea Treatment in Chemotherapy | data.frame | 2 | 4 |
ChildSpeaks | Stat2Data | Age at First Speaking | data.frame | 21 | 3 |
ClintonSanders | Stat2Data | Clinton/Sanders Primary Results (2016) | data.frame | 31 | 5 |
Clothing | Stat2Data | Sales for a Clothing Retailer | data.frame | 60 | 8 |
CloudSeeding | Stat2Data | Cloud Seeding Experiment (Winter Only) | data.frame | 28 | 7 |
CloudSeeding2 | Stat2Data | Cloud Seeding Experiment (Four Seasons) | data.frame | 108 | 8 |
Contraceptives | Stat2Data | Drug Interaction with Contraceptives | data.frame | 44 | 6 |
CountyHealth | Stat2Data | County Health Resources | data.frame | 53 | 4 |
CrabShip | Stat2Data | Crab Oxygen Intake | data.frame | 34 | 3 |
CrackerFiber | Stat2Data | Effects of Cracker Fiber on Digested Calories | data.frame | 48 | 3 |
CreditRisk | Stat2Data | Overdrawn Checking Account? | data.frame | 450 | 4 |
Cuckoo | Stat2Data | Measurements of Cuckoo Eggs | data.frame | 120 | 2 |
Day1Survey | Stat2Data | First Day Survey of Statistics Students | data.frame | 43 | 13 |
DiabeticDogs | Stat2Data | Lactic Acid Turnover in Dogs | data.frame | 20 | 4 |
Diamonds | Stat2Data | Characteristics of a Sample of Diamonds | data.frame | 351 | 6 |
Diamonds2 | Stat2Data | Characteristics of a Subset of the Diamond Sample | data.frame | 307 | 6 |
Dinosaurs | Stat2Data | Iridium Levels in Rock Layers to Investigate Dinosaur Extinction | data.frame | 28 | 4 |
Election08 | Stat2Data | 2008 U.S. Presidential Election | data.frame | 51 | 7 |
Election16 | Stat2Data | 2016 U.S. Presidential Election | data.frame | 50 | 8 |
ElephantsFB | Stat2Data | Measurements of Male African Elephants | data.frame | 138 | 3 |
ElephantsMF | Stat2Data | Measurements of African Elephants | data.frame | 288 | 3 |
Ethanol | Stat2Data | Effects of Oxygen on Sugar Metabolism | data.frame | 16 | 3 |
Eyes | Stat2Data | Pupil Dilation and Sexual Orientation | data.frame | 106 | 4 |
FGByDistance | Stat2Data | Results of NFL Field Goal Attempts | data.frame | 51 | 7 |
Faces | Stat2Data | Facial Attractiveness of Men | data.frame | 38 | 5 |
FaithfulFaces | Stat2Data | Faithfulness from a Photo? | data.frame | 170 | 7 |
FantasyBaseball | Stat2Data | Selection Times in a Fantasy Baseball Draft | data.frame | 24 | 9 |
FatRats | Stat2Data | Diet and Weight of Rats | data.frame | 60 | 3 |
Fertility | Stat2Data | Fertility Data for Women Having Trouble Getting Pregnant | data.frame | 333 | 10 |
Film | Stat2Data | Film Data from Leonard Maltin's Guide | data.frame | 100 | 9 |
FinalFourIzzo | Stat2Data | NCAA Final Four by Seed and Tom Izzo (through 2010) | data.frame | 1664 | 4 |
FinalFourIzzo17 | Stat2Data | NCAA Final Four by Seed and Tom Izzo (through 2017) | data.frame | 2112 | 4 |
FinalFourLong | Stat2Data | NCAA Final Four by Seed (Long Version through 2010) | data.frame | 2048 | 3 |
FinalFourLong17 | Stat2Data | NCAA Final Four by Seed (Long Version through 2017) | data.frame | 2496 | 3 |
FinalFourShort | Stat2Data | CAA Final Four by Seed (Short Version through 2010) | data.frame | 512 | 4 |
FinalFourShort17 | Stat2Data | NCAA Final Four by Seed (Short Version through 2017) | data.frame | 624 | 4 |
Fingers | Stat2Data | Finger Tap Rates | data.frame | 12 | 3 |
FirstYearGPA | Stat2Data | First Year GPA for College Students | data.frame | 219 | 10 |
FishEggs | Stat2Data | Fertility of Fish Eggs | data.frame | 35 | 4 |
Fitch | Stat2Data | Body Measurements of Mammal Species | data.frame | 28 | 5 |
FlightResponse | Stat2Data | Response of Migratory Geese to Helicopter Overflights | data.frame | 464 | 7 |
FloridaDP | Stat2Data | Florida Death Penalty Cases | data.frame | 326 | 4 |
Fluorescence | Stat2Data | Measuring Calcium Binding to Proteins | data.frame | 51 | 2 |
FranticFingers | Stat2Data | Finger Tap Rates | data.frame | 12 | 4 |
FruitFlies | Stat2Data | Fruit Fly Sexual Activity and Longevity | data.frame | 125 | 7 |
FruitFlies2 | Stat2Data | Fruit Fly Sexual Activity and Male Competition | data.frame | 201 | 7 |
FunnelDrop | Stat2Data | Funnel Drop Times | data.frame | 120 | 3 |
GlowWorms | Stat2Data | Female Glow-worms | data.frame | 26 | 2 |
Goldenrod | Stat2Data | Goldenrod Galls | data.frame | 1055 | 9 |
GrinnellHouses | Stat2Data | House Sales in Grinnell, Iowa | data.frame | 929 | 15 |
Grocery | Stat2Data | Grocery Sales and Discounts | data.frame | 36 | 5 |
Gunnels | Stat2Data | Are Gunnels Present at Shoreline? | data.frame | 1592 | 10 |
Handwriting | Stat2Data | Guess Author's Sex from Handwriting? | data.frame | 204 | 8 |
HawkTail | Stat2Data | Tail Lengths of Hawks | data.frame | 838 | 2 |
HawkTail2 | Stat2Data | Tail Lengths of Hawks (Unstacked) | data.frame | 577 | 2 |
Hawks | Stat2Data | Measurements on Three Hawk Species | data.frame | 908 | 19 |
HearingTest | Stat2Data | Correctly Identified Words in a Hearing Test | data.frame | 96 | 3 |
HeatingOil | Stat2Data | Heating Oil Consumption | data.frame | 408 | 4 |
HighPeaks | Stat2Data | Characteristics of Adirondack Hiking Trails | data.frame | 46 | 6 |
Hoops | Stat2Data | Grinnell College Basketball Games | data.frame | 147 | 22 |
HorsePrices | Stat2Data | Prices of Horses | data.frame | 50 | 5 |
Houses | Stat2Data | House Prices, Sizes, and Lot Areas | data.frame | 20 | 3 |
HousesNY | Stat2Data | House Prices in Rural NY | data.frame | 53 | 5 |
ICU | Stat2Data | Intensive Care Unit Patients | data.frame | 200 | 9 |
IQGuessing | Stat2Data | Guess IQ from a Photo? | data.frame | 40 | 3 |
InfantMortality2010 | Stat2Data | Infant Mortality Rates | data.frame | 10 | 2 |
Inflation | Stat2Data | Monthly Consumer Price Index (2009-2016) | data.frame | 96 | 5 |
InsuranceVote | Stat2Data | Congressional Votes on a Health Insurance Bill | data.frame | 435 | 9 |
Jurors | Stat2Data | Reporting Rates for Jurors | data.frame | 52 | 4 |
Kershaw | Stat2Data | Kershaw Pitch Data | data.frame | 3402 | 24 |
KeyWestWater | Stat2Data | Key West Water Temperatures | data.frame | 6572 | 3 |
Kids198 | Stat2Data | Body Measurements of Children | data.frame | 198 | 5 |
LeafWidth | Stat2Data | Leaf Measurements | data.frame | 252 | 5 |
Leafhoppers | Stat2Data | Leafhopper Diet and Longevity | data.frame | 8 | 3 |
Leukemia | Stat2Data | Responses to Treatment for Leukemia | data.frame | 51 | 9 |
LeveeFailures | Stat2Data | Levee Failures along the Mississippi River | data.frame | 82 | 14 |
LewyBody2Groups | Stat2Data | Lewy Bodies and Dimentia | data.frame | 39 | 3 |
LewyDLBad | Stat2Data | Lewy Bodies and Dimentia with Alzheimer's | data.frame | 20 | 3 |
LongJumpOlympics | Stat2Data | Olympic Men's Long Jump Gold Medal Distance (1900 - 2008) | data.frame | 26 | 2 |
LongJumpOlympics2016 | Stat2Data | Olympic Men's Long Jump Gold Medal Distance (1900 - 2016) | data.frame | 28 | 2 |
LosingSleep | Stat2Data | Sleep Hours for Teenagers | data.frame | 446 | 3 |
LostLetter | Stat2Data | Return Rates for "Lost" Letters | data.frame | 140 | 8 |
MLB2007Standings | Stat2Data | Standings and Team Statistics from the 2007 Baseball Season | data.frame | 30 | 21 |
MLBStandings2016 | Stat2Data | MLB Standings in 2016 | data.frame | 30 | 21 |
Marathon | Stat2Data | Daily Training for a Marathon Runner | data.frame | 1127 | 9 |
Markets | Stat2Data | Daily Change in Dow Jones and Nikkei Stock Market Indices | data.frame | 56 | 5 |
MathEnrollment | Stat2Data | Enrollments in Math Courses | data.frame | 11 | 3 |
MathPlacement | Stat2Data | Math Placement Exam Results | data.frame | 2696 | 16 |
MedGPA | Stat2Data | GPA and Medical School Admission | data.frame | 55 | 11 |
Meniscus | Stat2Data | Meniscus Repair Methods | data.frame | 18 | 4 |
MentalHealth | Stat2Data | Mental Health Admissions | data.frame | 36 | 3 |
MetabolicRate | Stat2Data | Metabolic Rate of Caterpillars | data.frame | 305 | 7 |
MetroCommutes | Stat2Data | Commute Times | data.frame | 2000 | 3 |
MetroHealth83 | Stat2Data | Health Services in Metropolitan Areas | data.frame | 83 | 16 |
Migraines | Stat2Data | Migraines and TMS | data.frame | 2 | 4 |
Milgram | Stat2Data | Ethics and a Milgram Experiment | data.frame | 37 | 2 |
MothEggs | Stat2Data | Moth Eggs | data.frame | 39 | 2 |
MouseBrain | Stat2Data | Effects of Serotonin in Mice | data.frame | 48 | 3 |
MusicTime | Stat2Data | Estimating Time with Different Music Playing | data.frame | 60 | 6 |
NCbirths | Stat2Data | North Carolina Birth Records | data.frame | 1450 | 15 |
NFL2007Standings | Stat2Data | NFL Standings for 2007 Regular Season | data.frame | 32 | 10 |
NFLStandings2016 | Stat2Data | NFL Standings for 2016 Regular Season | data.frame | 32 | 11 |
Nursing | Stat2Data | Nursing Homes | data.frame | 52 | 7 |
OilDeapsorbtion | Stat2Data | Effect of Ultrasound on Oil Deapsorbtion | data.frame | 40 | 4 |
Olives | Stat2Data | Fenthion in Olive Oil | data.frame | 18 | 7 |
Orings | Stat2Data | Space Shuttle O-Rings | data.frame | 24 | 2 |
Overdrawn | Stat2Data | Overdrawn Checking Account? | data.frame | 450 | 4 |
Oysters | Stat2Data | Size of Oysters | data.frame | 30 | 5 |
PKU | Stat2Data | Dopamine levels with PKU in diets | data.frame | 20 | 4 |
PalmBeach | Stat2Data | Palm Beach Butterfly Ballot | data.frame | 67 | 3 |
PeaceBridge2003 | Stat2Data | Monthly Peace Bridge Traffic ( 2003-2015) | data.frame | 156 | 4 |
PeaceBridge2012 | Stat2Data | Monthly Peace Bridge Traffic ( 2012-2015) | data.frame | 48 | 4 |
Pedometer | Stat2Data | Pedometer Walking Data | data.frame | 68 | 8 |
Perch | Stat2Data | Perch Sizes | data.frame | 56 | 4 |
PigFeed | Stat2Data | Additives in Pig Feed | data.frame | 12 | 3 |
Pines | Stat2Data | Measurements of Pine Tree Seedlings | data.frame | 1000 | 15 |
Political | Stat2Data | Political Behavior of College Students | data.frame | 59 | 9 |
Pollster08 | Stat2Data | 2008 U.S. Presidential Election Polls | data.frame | 102 | 11 |
Popcorn | Stat2Data | Popcorn Popping Success | data.frame | 12 | 3 |
PorscheJaguar | Stat2Data | Porsche and Jaguar Prices | data.frame | 60 | 5 |
PorschePrice | Stat2Data | Porsche Prices | data.frame | 30 | 3 |
Pulse | Stat2Data | Pulse Rates and Exercise | data.frame | 232 | 7 |
Putts1 | Stat2Data | Putting Success by Length (Long Form) | data.frame | 587 | 2 |
Putts2 | Stat2Data | Putting Success by Length (Short Form) | data.frame | 5 | 4 |
Putts3 | Stat2Data | Hypothetical Putting Data (Short Form) | data.frame | 5 | 4 |
RacialAnimus | Stat2Data | Racial Animus and City Demgraphics | data.frame | 196 | 7 |
RadioactiveTwins | Stat2Data | Comparing Twins Ability to Clear Radioactive Particles | data.frame | 30 | 3 |
RailsTrails | Stat2Data | Homes in Northampton MA Near Rail Trails | data.frame | 104 | 30 |
Rectangles | Stat2Data | Measurements of Rectangles | data.frame | 9 | 5 |
ReligionGDP | Stat2Data | Religion and GDP for Countries | data.frame | 44 | 9 |
RepeatedPulse | Stat2Data | Pulse Rates at Various Times of Day | data.frame | 104 | 3 |
ResidualOil | Stat2Data | US Residual Oil Production (Quarterly 1983-2016) | data.frame | 136 | 5 |
Retirement | Stat2Data | Yearly Contributions to a Supplemental Retirement Account | data.frame | 16 | 2 |
Ricci | Stat2Data | Firefighter Promotion Exam Scores | data.frame | 118 | 5 |
RiverElements | Stat2Data | Elements in River Water Samples | data.frame | 12 | 27 |
RiverIron | Stat2Data | Iron in River Water Samples | data.frame | 12 | 4 |
SATGPA | Stat2Data | SAT Scores and GPA | data.frame | 24 | 3 |
SampleFG | Stat2Data | Field Goal Attempts in the NFL | data.frame | 30 | 13 |
SandwichAnts | Stat2Data | Ants on Sandwiches | data.frame | 48 | 5 |
SeaIce | Stat2Data | Arctic Sea Ice (1979-2015) | data.frame | 37 | 4 |
SeaSlugs | Stat2Data | Sea Slug Larvae | data.frame | 36 | 2 |
SleepingShrews | Stat2Data | Shrew Heart Rates at Stages of Sleep | data.frame | 18 | 4 |
Sparrows | Stat2Data | Sparrow Measurements | data.frame | 116 | 3 |
SpeciesArea | Stat2Data | Land Area and Mammal Species | data.frame | 14 | 5 |
Speed | Stat2Data | Highway Fatality Rates (Yearly) | data.frame | 21 | 3 |
SugarEthanol | Stat2Data | Effects of Oxygen on Sugar Metabolism | data.frame | 16 | 3 |
SuicideChina | Stat2Data | Suicide Attempts in Shandong, China | data.frame | 2571 | 11 |
Swahili | Stat2Data | Attitudes Towards Swahili in Kenyan Schools | data.frame | 480 | 4 |
TMS | Stat2Data | Migraines and TMS | data.frame | 2 | 4 |
Tadpoles | Stat2Data | Effects of a Fungus on Tadpoles | data.frame | 27 | 4 |
TechStocks | Stat2Data | Daily Prices of Three Tech Stocks | data.frame | 504 | 5 |
TeenPregnancy | Stat2Data | State Teen Pregnancy Rates | data.frame | 50 | 4 |
TextPrices | Stat2Data | Textbook Prices | data.frame | 30 | 2 |
ThomasConfirmation | Stat2Data | US Senate Votes on Clarence Thomas Confirmation | data.frame | 100 | 6 |
ThreeCars | Stat2Data | Prices of Three Used Car Models (2007) | data.frame | 90 | 8 |
ThreeCars2017 | Stat2Data | Price, Age, and Mileage of Three Used Car Models | data.frame | 90 | 7 |
TipJoke | Stat2Data | Improve Chances of Getting a Tip? | data.frame | 211 | 5 |
Titanic | Stat2Data | Passengers on the Titanic | data.frame | 1313 | 6 |
TomlinsonRush | Stat2Data | LaDainian Tomlinson Rushing Yards | data.frame | 16 | 4 |
TwinsLungs | Stat2Data | Comparing Twins Ability to Clear Radioactive Particles | data.frame | 14 | 3 |
USstamps | Stat2Data | Price of US Stamps | data.frame | 25 | 2 |
Undoing | Stat2Data | Defense of Undoing OCD Symptoms in Psychotherapy | data.frame | 44 | 3 |
VisualVerbal | Stat2Data | Visual versus Verbal Performance | data.frame | 80 | 5 |
Volts | Stat2Data | Voltage Drop for a Discharging Capacitor | data.frame | 50 | 2 |
WalkTheDogs | Stat2Data | Did the Author Walk the Dogs Today? | data.frame | 223 | 7 |
WalkingBabies | Stat2Data | Effects of Exercise on First Walking | data.frame | 24 | 2 |
WeightLossIncentive | Stat2Data | Do Financial Incentives Improve Weight Loss? | data.frame | 38 | 3 |
WeightLossIncentive4 | Stat2Data | Do Financial Incentives Improve Weight Loss? (4 Months) | data.frame | 36 | 2 |
WeightLossIncentive7 | Stat2Data | Do Financial Incentives Improve Weight Loss? (7 Months) | data.frame | 33 | 2 |
Whickham2 | Stat2Data | Whickham Health Study | data.frame | 1314 | 5 |
WordMemory | Stat2Data | Experiment on Word Memory | data.frame | 40 | 4 |
WordsWithFriends | Stat2Data | Words with Friends Scores | data.frame | 444 | 11 |
Wrinkle | Stat2Data | Moving Wet Objects with Wrinkled Fingers | data.frame | 80 | 7 |
YouthRisk | Stat2Data | Annual survey of health-risk youth behaviors | data.frame | 13387 | 6 |
YouthRisk2007 | Stat2Data | Riding with a Driver Who Has Been Drinking | data.frame | 13387 | 6 |
YouthRisk2009 | Stat2Data | Youth Risk Survey | data.frame | 500 | 6 |
Zimmerman | Stat2Data | Stand Your Ground Simpson's Paradox | data.frame | 220 | 5 |
US30 | ROI | Monthly return data for 30 of the largest US stocks | matrix | 180 | 30 |
biocOrg_name | genekitr | Datasets geneList entrez gene list with decreasing fold change value | data.frame | 18 | 2 |
deg | genekitr | Datasets geneList entrez gene list with decreasing fold change value | data.frame | 18039 | 10 |
ensOrg_name | genekitr | Datasets geneList entrez gene list with decreasing fold change value | data.frame | 317 | 4 |
geneList | genekitr | Datasets geneList entrez gene list with decreasing fold change value | numeric | | |
hsapiens_probe_platform | genekitr | Datasets geneList entrez gene list with decreasing fold change value | data.frame | 36 | 3 |
keggOrg_name | genekitr | Datasets geneList entrez gene list with decreasing fold change value | data.frame | 7254 | 2 |
msig_category | genekitr | Datasets geneList entrez gene list with decreasing fold change value | data.frame | 23 | 2 |
msig_org | genekitr | Datasets geneList entrez gene list with decreasing fold change value | data.frame | 20 | 2 |
MMRcoverageDE | surveillance | MMR coverage levels in the 16 states of Germany | data.frame | 19 | 5 |
abattoir | surveillance | Abattoir Data | sts | | |
campyDE | surveillance | Campylobacteriosis and Absolute Humidity in Germany 2002-2011 | data.frame | 522 | 12 |
deleval | surveillance | Surgical Failures Data | sts | | |
fluBYBW | surveillance | Influenza in Southern Germany | sts | | |
fooepidata | surveillance | Toy Data for 'twinSIR' | epidata | 17800 | 13 |
h1_nrwrp | surveillance | RKI SurvStat Data | disProg | | |
ha | surveillance | Hepatitis A in Berlin | disProg | | |
ha.sts | surveillance | Hepatitis A in Berlin | sts | | |
hagelloch | surveillance | 1861 Measles Epidemic in the City of Hagelloch, Germany | epidata | 70500 | 16 |
hagelloch.df | surveillance | 1861 Measles Epidemic in the City of Hagelloch, Germany | data.frame | 188 | 26 |
hepatitisA | surveillance | Hepatitis A in Germany | disProg | | |
husO104Hosp | surveillance | Hospitalization date for HUS cases of the STEC outbreak in Germany, 2011 | data.frame | 630 | 2 |
imdepi | surveillance | Occurrence of Invasive Meningococcal Disease in Germany | epidataCS | | |
imdepifit | surveillance | Example 'twinstim' Fit for the 'imdepi' Data | twinstim | | |
influMen | surveillance | Influenza and meningococcal infections in Germany, 2001-2006 | disProg | | |
k1 | surveillance | RKI SurvStat Data | disProg | | |
m1 | surveillance | RKI SurvStat Data | disProg | | |
m2 | surveillance | RKI SurvStat Data | disProg | | |
m3 | surveillance | RKI SurvStat Data | disProg | | |
m4 | surveillance | RKI SurvStat Data | disProg | | |
m5 | surveillance | RKI SurvStat Data | disProg | | |
measles.weser | surveillance | Measles in the Weser-Ems region of Lower Saxony, Germany, 2001-2002 | disProg | | |
measlesDE | surveillance | Measles in the 16 states of Germany | sts | | |
measlesWeserEms | surveillance | Measles in the Weser-Ems region of Lower Saxony, Germany, 2001-2002 | sts | | |
meningo.age | surveillance | Meningococcal infections in France 1985-1997 | disProg | | |
momo | surveillance | Danish 1994-2008 all-cause mortality data for eight age groups | sts | | |
n1 | surveillance | RKI SurvStat Data | disProg | | |
n2 | surveillance | RKI SurvStat Data | disProg | | |
q1_nrwh | surveillance | RKI SurvStat Data | disProg | | |
q2 | surveillance | RKI SurvStat Data | disProg | | |
rotaBB | surveillance | Rotavirus cases in Brandenburg, Germany, during 2002-2013 stratified by 5 age categories | sts | | |
s1 | surveillance | RKI SurvStat Data | disProg | | |
s2 | surveillance | RKI SurvStat Data | disProg | | |
s3 | surveillance | RKI SurvStat Data | disProg | | |
salmAllOnset | surveillance | Salmonella cases in Germany 2001-2014 by data of symptoms onset | sts | | |
salmHospitalized | surveillance | Hospitalized Salmonella cases in Germany 2004-2014 | sts | | |
salmNewport | surveillance | Salmonella Newport cases in Germany 2004-2013 | sts | | |
salmonella.agona | surveillance | Salmonella Agona cases in the UK 1990-1995 | disProg | | |
shadar | surveillance | Salmonella Hadar cases in Germany 2001-2006 | disProg | | |
stsNewport | surveillance | Salmonella Newport cases in Germany 2001-2015 | sts | | |
cohab_MixMat | ergm | Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent | matrix | 5 | 5 |
cohab_PopWts | ergm | Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent | data.frame | 655 | 8 |
cohab_TargetStats | ergm | Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent | numeric | | |
ecoli1 | ergm | Two versions of an E. Coli network dataset | network | | |
ecoli2 | ergm | Two versions of an E. Coli network dataset | network | | |
faux.desert.high | ergm | Faux desert High School as a network object | network | | |
faux.dixon.high | ergm | Faux dixon High School as a network object | network | | |
faux.magnolia.high | ergm | Goodreau's Faux Magnolia High School as a network object | network | | |
faux.mesa.high | ergm | Goodreau's Faux Mesa High School as a network object | network | | |
flobusiness | ergm | Florentine Family Marriage and Business Ties Data as a "network" object | network | | |
flomarriage | ergm | Florentine Family Marriage and Business Ties Data as a "network" object | network | | |
g4 | ergm | Goodreau's four node network as a "network" object | network | | |
kapferer | ergm | Kapferer's tailor shop data | network | | |
kapferer2 | ergm | Kapferer's tailor shop data | network | | |
molecule | ergm | Synthetic network with 20 nodes and 28 edges | network | | |
samplike | ergm | Cumulative network of positive affection within a monastery as a "network" object | network | | |
samplk1 | ergm | Longitudinal networks of positive affection within a monastery as a "network" object | network | | |
samplk2 | ergm | Longitudinal networks of positive affection within a monastery as a "network" object | network | | |
samplk3 | ergm | Longitudinal networks of positive affection within a monastery as a "network" object | network | | |
exfm1 | forestmangr | Stratified random inventory pilot data | tbl_df | 22 | 5 |
exfm10 | forestmangr | Inventory data of an eucalyptus forest Brazil with dominant height variable | tbl_df | 895 | 15 |
exfm11 | forestmangr | Observed hieght values of trees, and estimated values using 3 different models | tbl_df | 199 | 6 |
exfm12 | forestmangr | Inventory data of an eucalyptus forest in Brazil, with age and site variables | tbl_df | 139 | 8 |
exfm13 | forestmangr | Experimental data on nitrogen effect in species fertilizing | tbl_df | 36 | 7 |
exfm14 | forestmangr | Inventory data of an eucalyptus forest in Brazil, with age and dominant height variables | tbl_df | 859 | 4 |
exfm15 | forestmangr | Simplified Inventory data of an eucalyptus forest in Brazil | tbl_df | 900 | 7 |
exfm16 | forestmangr | Inventory data of an eucalyptus forest in Brazil, with age variable | tbl_df | 139 | 7 |
exfm17 | forestmangr | Inventory data of an eucalyptus forest in Brazil, with age and site variables | tbl_df | 139 | 8 |
exfm18 | forestmangr | Experimental data on nitrogen effect in species fertilizing | tbl_df | 877 | 6 |
exfm19 | forestmangr | Volume of felled trees, measured in the Smalian method | tbl_df | 197 | 8 |
exfm2 | forestmangr | Stratified random inventory definite data | tbl_df | 57 | 5 |
exfm20 | forestmangr | Inventory data of a natural forest in Brazil | tbl_df | 12295 | 18 |
exfm21 | forestmangr | Inventory data of an eucalyptus forest in Brazil | tbl_df | 900 | 13 |
exfm22 | forestmangr | Revenue data if an eucalyptus forest | tbl_df | 8 | 3 |
exfm3 | forestmangr | Simple random inventory pilot data | tbl_df | 10 | 4 |
exfm4 | forestmangr | Simple random inventory definite data | tbl_df | 25 | 3 |
exfm5 | forestmangr | Systematic inventory data | tbl_df | 18 | 4 |
exfm6 | forestmangr | Stratified random inventory definite data 2 | tbl_df | 10 | 15 |
exfm7 | forestmangr | Data of felled trees sections, measured in the Smalian method | tbl_df | 3393 | 11 |
exfm8 | forestmangr | Data of felled trees sections, measured in the Huber method | tbl_df | 596 | 10 |
exfm9 | forestmangr | Inventory data of an eucalyptus forest in minas gerais, Brazil | tbl_df | 900 | 14 |
exStudy | PAMpal | Example AcousticStudy Object | AcousticStudy | | |
testCeps | PAMpal | A fake cepstrum contour | list | | |
testClick | PAMpal | A two-channel recording of a delphinid click | list | | |
testGPL | PAMpal | A fake GPL detection | list | | |
testWhistle | PAMpal | A fake whistle contour | list | | |
E1684 | hdbayes | ECOG E1684 Trial | data.frame | 262 | 8 |
E1690 | hdbayes | ECOG E1690 Trial | data.frame | 426 | 8 |
E1694 | hdbayes | ECOG E1694 Trial | data.frame | 200 | 6 |
E2696 | hdbayes | ECOG E2696 Trial | data.frame | 105 | 6 |
IBCSG_curr | hdbayes | International Breast Cancer Study Group (IBCSG) Trial VI Data | tbl_df | 488 | 8 |
IBCSG_hist | hdbayes | International Breast Cancer Study Group (IBCSG) Trial VI Data | tbl_df | 103 | 8 |
actg019 | hdbayes | AIDS Clinical Trial ACTG019 | data.frame | 822 | 5 |
actg036 | hdbayes | AIDS Clinical Trial ACTG036 | data.frame | 183 | 5 |
territories | arealDB | Example 'gazetteer' | onto | | |
pop_dat | ageutils | Aggregated population data | data.frame | 19 | 4 |
example_data_1_subject | iglu | Example CGM data for one subject with Type II diabetes | data.frame | 2915 | 3 |
example_data_5_subject | iglu | Example CGM data for 5 subjects with Type II diabetes | data.frame | 13866 | 3 |
example_data_hall | iglu | Example data from Hall et al. (2018) | spec_tbl_df | 34890 | 4 |
example_meals_hall | iglu | Example mealtimes data from Hall et al. (2018) | tbl_df | 9 | 3 |
basedata | troopdata | Vine's U.S. basing data | tbl_df | 414 | 9 |
builddata | troopdata | U.S. Military overseas construction spending data | spec_tbl_df | 5532 | 8 |
troopdata_rebuild_long | troopdata | U.S. overseas troop deployment data | tbl_df | 20139 | 29 |
troopdata_rebuild_reports | troopdata | DMDC Deployment Reports | tbl_df | 15427 | 52 |
nflfastr_stat_mapping | ffscrapr | Mappings for nflfastr to fantasy platform scoring | data.frame | 143 | 3 |
dbces11 | netrankr | dbces11 graph | igraph | | |
florentine_m | netrankr | Florentine family marriage network | igraph | | |
MoscowMtStJoe | yaImpute | Moscow Mountain and St. Joe Woodlands (Idaho, USA) Tree and LiDAR Data | data.frame | 165 | 64 |
TallyLake | yaImpute | Tally Lake, Flathead National Forest, Montana, USA | data.frame | 847 | 29 |
AUCO | patterncausality | A data from Illapel | data.frame | 32 | 5 |
DJS | patterncausality | Dow Jones stock price | data.frame | 4510 | 30 |
climate | patterncausality | Climate index | data.frame | 535 | 5 |
capesData | capesData | Data on Scholarships in CAPES International Mobility Programs | tbl_df | 146036 | 14 |
capesData_raw | capesData | Data on Scholarships in CAPES International Mobility Programs | tbl_df | 146036 | 51 |
bandwidth.chrisproba | PEcAnRTM | | data.frame | 62 | 4 |
dataSpec_prospectd | PEcAnRTM | | matrix | 2101 | 8 |
fwhm.aviris.classic | PEcAnRTM | | data.frame | 224 | 2 |
fwhm.aviris.ng | PEcAnRTM | | data.frame | 480 | 5 |
fwhm.hyperion | PEcAnRTM | | list | | |
model.list | PEcAnRTM | | data.frame | 6 | 5 |
rsr.avhrr | PEcAnRTM | | matrix | 503 | 4 |
rsr.landsat5 | PEcAnRTM | | matrix | 914 | 7 |
rsr.landsat7 | PEcAnRTM | | matrix | 914 | 7 |
rsr.landsat8 | PEcAnRTM | | matrix | 825 | 8 |
rsr.modis | PEcAnRTM | | matrix | 1820 | 8 |
rsr.viirs | PEcAnRTM | | matrix | 2500 | 11 |
sensor.rsr | PEcAnRTM | | list | | |
testspec_ACRU | PEcAnRTM | | matrix | 2101 | 78 |
county_month_birth_rate_2005_version | Wats | Monthly Growth Fertility Rates (GFR) for 12 urban Oklahoma counties | tbl_df | 1440 | 12 |
county_month_birth_rate_2014_version | Wats | Monthly Growth Fertility Rates (GFR) for 12 urban Oklahoma counties | tbl_df | 1440 | 12 |
gaa | k5 | GAA Team Abbreviations by Season and Team ID | tbl_df | 94 | 3 |
commits | jqr | GitHub Commits Data | character | | |
anno | kangar00 | Example annotation file for three pathways. | data.frame | 4056 | 5 |
geno | kangar00 | Example genotypes for 50 individuals. | matrix | 50 | 4056 |
gwas | kangar00 | Example 'GWASdata' object. | GWASdata | | |
hsa04020 | kangar00 | Example 'pathway' object for pathway hsa04020. | pathway | | |
hsa04022_info | kangar00 | Example 'pathway_info' object for 'pathway' hsa04022. | pathway_info | | |
lkmt.net.kernel.hsa04020 | kangar00 | Example test result for the network-based 'kernel' for 'pathway' hsa04020. | lkmt | | |
net.kernel.hsa04020 | kangar00 | Example network-based kernel matrix for pathway hsa04020. | kernel | | |
pheno | kangar00 | Example phenotype file for 50 individuals. | data.frame | 50 | 3 |
rs10243170_info | kangar00 | Example 'snp_info' object for SNP rs10243170. | snp_info | | |
BADM | PEcAn.data.land | Biomass and soil data from FluxNet sites | data.frame | 12300 | 13 |
iscn_soc | PEcAn.data.land | Soil organic carbon (SOC) density based on eco-region level 2 code from the ISCN database. | matrix | 200 | 43 |
soil_class | PEcAn.data.land | Default parameters for calculating soil properties from sand & clay content | list | | |
sibcasa_output_vars | PEcAn.SIBCASA | Output variables for SIBCASA | data.frame | 131 | 6 |
co2.1850.2020 | PEcAn.LPJGUESS | | data.frame | 171 | 2 |
lake | elevatr | SpatialPolygonsDataFrame of Lake Sunapee | sf | 1 | 14 |
pt_df | elevatr | Small data frame of xy locations | data.frame | 5 | 2 |
sf_big | elevatr | A sf POINT dataset of random points | sf | 250 | 1 |
barley | paar | Barley grain yield | data.frame | 7394 | 3 |
wheat | paar | Database from a production field under continuous agriculture | data.frame | 5982 | 7 |
fish | parameters | Sample data set | data.frame | 250 | 9 |
qol_cancer | parameters | Sample data set |