Tengeler2020_pq | MiscMetabar | This tutorial explores the dataset from Tengeler et al. (2020) available in the 'mia' package. obtained using 'mia::makePhyloseqFromTreeSE(Tengeler2020)' | phyloseq | | |
data_fungi | MiscMetabar | Fungal OTU in phyloseq format | phyloseq | | |
data_fungi_mini | MiscMetabar | Fungal OTU in phyloseq format | phyloseq | | |
data_fungi_sp_known | MiscMetabar | Fungal OTU in phyloseq format | phyloseq | | |
faketrial | wrappedtools | Results from a simulated clinical trial with interaction effects. | tbl_df | 300 | 24 |
SGPstateData | SGP | State assessment program data from large scale state assessments for use with SGP package | environment | | |
data_disa_uid_map | sismar | UID map for linking DISA, SISMA and DATIM | tbl_df | 2080 | 3 |
data_sisma_geo_above_site | sismar | Map for linking province and district shape codes to SISMA data | tbl_df | 161 | 4 |
data_sisma_geo_sites | sismar | Map for linking geocoordinates to SISMA health facility data | tbl_df | 1646 | 3 |
data_sisma_sitelist | sismar | Deduplicated SISMA site list | tbl_df | 2241 | 5 |
fmhfit | ergm.ego | Fitted ergm.ego model object | ergm.ego | | |
CDC | cNORM | BMI growth curves from age 2 to 25 | data.frame | 45035 | 7 |
elfe | cNORM | Sentence completion test from ELFE 1-6 | data.frame | 1400 | 3 |
ppvt | cNORM | Vocabulary development from 2.5 to 17 | data.frame | 4542 | 6 |
allGalaxies | admix | Measurements of heliocentric velocities in four galaxies | data.frame | 8862 | 3 |
milkyWay | admix | Heliocentric velocity for the Milky Way | data.frame | 170601 | 1 |
mortality_sample | admix | Deaths statistics in 11 european countries | list | | |
stmf_small | admix | Short-term Mortality Fluctuations (STMF) data | data.frame | 15252 | 19 |
algae | aaltobda | algae | integer | | |
bioassay | aaltobda | bioassay | data.frame | 4 | 3 |
bioassay_posterior | aaltobda | bioassay_posterior | data.frame | 4000 | 2 |
drowning | aaltobda | drowning | data.frame | 44 | 2 |
factory | aaltobda | factory | data.frame | 5 | 6 |
kilpisjarvi | aaltobda | kilpisjarvi | data.frame | 62 | 5 |
kilpisjarvi2022 | aaltobda | kilpisjarvi2022 | data.frame | 71 | 5 |
windshieldy1 | aaltobda | windshieldy1 | numeric | | |
windshieldy2 | aaltobda | windshieldy2 | numeric | | |
MaskOri | statConfR | Data of 16 participants in a masked orientation discrimination experiment (Hellmann et al., 2023, Exp. 1) | data.frame | 25920 | 6 |
holes | cocons | Holes Data Set | list | | |
holes_bm | cocons | Holes with trend + multiple realizations Data Set | list | | |
stripes | cocons | Stripes Data Set | list | | |
BaseDataSet.ConversionFactors | Luminescence | Base data set of dose-rate conversion factors | list | | |
BaseDataSet.FractionalGammaDose | Luminescence | Base data set of fractional gamma-dose values | list | | |
BaseDataSet.GrainSizeAttenuation | Luminescence | Base dataset for grain size attenuation data by Guérin et al. (2012) | data.frame | 16 | 7 |
CWOSL.SAR.Data | Luminescence | Example data from a SAR OSL and SAR TL measurement for the package Luminescence | Risoe.BINfileData | | |
CW_Curve.BosWallinga2012 | Luminescence | Example CW-OSL curve data for the package Luminescence | data.frame | 2000 | 2 |
ExampleData.CW_OSL_Curve | Luminescence | Example CW-OSL curve data for the package Luminescence | data.frame | 1000 | 2 |
ExampleData.CobbleData | Luminescence | Example data for calc_CobbleDoseRate() | data.frame | 14 | 24 |
ExampleData.DeValues | Luminescence | Example De data sets for the package Luminescence | list | | |
ExampleData.Fading | Luminescence | Example data for feldspar fading measurements | list | | |
ExampleData.RLum.Data.Image | Luminescence | Example data as RLum.Data.Image objects | RLum.Data.Image | | |
ExampleData.ScaleGammaDose | Luminescence | Example data for scale_GammaDose() | data.frame | 9 | 12 |
ExampleData.SurfaceExposure | Luminescence | Example OSL surface exposure dating data | list | | |
ExampleData.TR_OSL | Luminescence | Example TR-OSL data | RLum.Data.Curve | | |
ExampleData.portableOSL | Luminescence | Example portable OSL curve data for the package Luminescence | list | | |
IRSAR.RF.Data | Luminescence | Example data as RLum.Analysis objects | RLum.Analysis | | |
Lx.data | Luminescence | Example Lx and Tx curve data from an artificial OSL measurement | data.frame | 100 | 2 |
LxTxData | Luminescence | Example Lx/Tx data from CW-OSL SAR measurement | data.frame | 7 | 4 |
OSL.SARMeasurement | Luminescence | Example data for a SAR OSL measurement and a TL spectrum using a lexsyg reader | list | | |
TL.SAR.Data | Luminescence | Example data from a SAR OSL and SAR TL measurement for the package Luminescence | Risoe.BINfileData | | |
TL.Spectrum | Luminescence | Example data for a SAR OSL measurement and a TL spectrum using a lexsyg reader | RLum.Data.Spectrum | | |
Tx.data | Luminescence | Example Lx and Tx curve data from an artificial OSL measurement | data.frame | 100 | 2 |
data_CrossTalk | Luminescence | Example Al2O3:C Measurement Data | list | | |
data_ITC | Luminescence | Example Al2O3:C Measurement Data | RLum.Analysis | | |
values.cosmic.Softcomp | Luminescence | Base data set for cosmic dose rate calculation | data.frame | 33 | 2 |
values.curve | Luminescence | Example data for fit_LMCurve() in the package Luminescence | data.frame | 4000 | 2 |
values.curveBG | Luminescence | Example data for fit_LMCurve() in the package Luminescence | data.frame | 4000 | 2 |
values.factor.Altitude | Luminescence | Base data set for cosmic dose rate calculation | data.frame | 7 | 2 |
values.par.FJH | Luminescence | Base data set for cosmic dose rate calculation | data.frame | 12 | 4 |
DCA1_GOA | paleoAM | Benthic Foram Abundances from the Gulf of Alaska Reported by Sharon et al 2021 | numeric | | |
abundData_GOA | paleoAM | Benthic Foram Abundances from the Gulf of Alaska Reported by Sharon et al 2021 | data.frame | 355 | 48 |
fullDataTable_GOA | paleoAM | Benthic Foram Abundances from the Gulf of Alaska Reported by Sharon et al 2021 | data.frame | 355 | 53 |
graptCommData | paleoAM | Katian-Hirnantian Graptolite Assemblages Reported by Sheets et al. (2016) | data.frame | 34 | 43 |
graptSampleInfo | paleoAM | Katian-Hirnantian Graptolite Assemblages Reported by Sheets et al. (2016) | data.frame | 34 | 5 |
HRQoL | forestplot | Regression coefficients and confidence intervals from HRQoL study | list | | |
dfHRQoL | forestplot | Regression coefficients and confidence intervals from HRQoL study | tbl_df | 8 | 5 |
. | weyl | Class "dot" | dot | | |
d | weyl | Generating elements for the first Weyl algebra | weyl | | |
x | weyl | Generating elements for the first Weyl algebra | weyl | | |
basicRelationships | ribd | Basic relationships | data.frame | 12 | 7 |
jicaque | ribd | Jicaque pedigree | data.frame | 22 | 4 |
transfers | EpiContactTrace | Movement Example Data | data.frame | 70190 | 6 |
endosim | npROCRegression | Simulated endocrine data. | data.frame | 2840 | 4 |
endosyn | ROCnReg | Simulated endocrine data. | data.frame | 2840 | 4 |
psa | ROCnReg | Prostate specific antigen (PSA) biomarker study. | data.frame | 683 | 6 |
wheatdata | SpATS | Wheat yield in South Australia | data.frame | 330 | 7 |
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 | | |
toydata | mstDIF | A Toy Example of 1000 Respondents Working on a Multistage Test | list | | |
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 |
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 |
fleet1 | dbglm | Data of vehicles registered in New Zealand as of November 2017 | tbl_df | 10000 | 6 |
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 |
simulated_data_1 | BayesBP | Generate simulated data 1 | list | | |
simulated_data_2 | BayesBP | Generate simulated data 2 | list | | |
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 |
mimeTypeExtensions | RCurl | Mapping from extension to MIME type | character | | |
assetReturns | JFE | Data Sets | xts | 2735 | 29 |
macrodata | JFE | Data Sets | xts | 669 | 4 |
eez_rg | oceanic | Eez Coefficients | sf | 243 | 16 |
port | oceanic | port position | SpatialPolygonsDataFrame | | |
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 |
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 | | |
data1 | speedglm | A toy dataset | data.frame | 100 | 4 |
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 | |
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 |
KnockoffHybrid.example | KnockoffHybrid | Example data for KnockoffHybrid | list | | |
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 |
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 |
Matches | EUfootball | Dataset Matches | data.frame | 24208 | 32 |
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 |
congress | ClusVis | Real categorical data set: Congressional Voting Records Data Set | data.frame | 435 | 17 |
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 | | |
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 |
gazelleRelocations | SyncMove | Relocations of Mongolian Gazelles | data.frame | 1747 | 5 |
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 | | |
polio | weightedCL | Polio cases in USA from Jan 1970 till Dec 1983 | numeric | | |
sleep | weightedCL | Infant sleep status data | data.frame | 1024 | 3 |
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 |
ACEdata | hapsim | ACE data set | data.frame | 22 | 52 |
moore | PAmeasures | Moore's Law data | data.frame | 48 | 3 |
dgrp2.3R.5k.data | GenomeAdmixR | A subset of sequencing data from the Drosophila Genetics Reference Panel | genomeadmixr_data | | |
DowJones | Copula.Markov | Dow Jones Industrial Average | data.frame | 754 | 1 |
bamExample | scruff | Example GAlignments Object | GAlignments | | |
barcodeExample | scruff | A vector of example cell barcodes. | character | | |
cbtop10000 | scruff | Top 10,000 rows for v1, v2, and v3 cell barcode whitelist files | data.table | 10000 | 3 |
sceExample | scruff | Example SingleCellExperiment Object | SingleCellExperiment | | |
validCb | scruff | Cell barcode whitelist (737K-august-2016.txt) | data.frame | 737280 | 1 |
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 |
docvisits | zic | Demand for Health Care Data | data.frame | 1812 | 23 |
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 |
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 | | |
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 |
Hedenfalk | Equalden.HD | Hedenfalk data | matrix | 3226 | 15 |
Rat | Equalden.HD | Rat data | data.frame | 8038 | 5 |
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 |
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 | | |
DecodeMap | IBDsim | Decode recombination map | list | | |
dominant1 | IBDsim | Autosomal dominant pedigree | matrix | 14 | 6 |
burposte | frontiles | Burposte data | data.frame | 9521 | 3 |
spain | frontiles | Spain data | data.frame | 61 | 4 |
rADTTE | teal.modules.hermes | Random Time to Event Analysis Dataset | tbl_df | 2000 | 67 |
mcompd | multilevelcoda | Multilevel Compositional Data | data.table | 3540 | 10 |
psub | multilevelcoda | Possible Pairwise Substitutions | data.table | 20 | 5 |
sbp | multilevelcoda | Sequential Binary Partition | matrix | 4 | 5 |
sim | multilevelcoda | multilevelcoda Simulation Study results | list | | |
EDpro | PROreg | Eating Disorders patient-reported outcome data. | data.frame | 525 | 18 |
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 | | |
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 | | |
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 | | |
LF.data | LogicForest | LF.data | data.frame | 200 | 52 |
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 |
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 |
benchmark64.data | bit64 | Results of performance measurement on a Core i7 Lenovo T410 8 GB RAM under Windows 7 64bit | matrix | 16 | 6 |
optimizer64.data | bit64 | Results of performance measurement on a Core i7 Lenovo T410 8 GB RAM under Windows 7 64bit | matrix | 8 | 2 |
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 |
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 |
specdat | LCF | Phosphorus K-edge XANES spectral data for LCF | list | | |
LSAT | testforDEP | LSAT dataset | data.frame | 82 | 3 |
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 |
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 | | |
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 | | |
teenpov | cglm | Data from the National Longitudinal Survey of Youth (NLSY). | data.frame | 1342 | 7 |
presidential_debates_2012 | textstem | 2012 U.S. Presidential Debates | tbl_df | 2912 | 5 |
sam_i_am | textstem | Sam I Am Text | character | | |
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 |
CV | labstats | Data to estimate the coefficient of variation | data.frame | 15 | 3 |
KH2004 | labstats | Repeated measures data on rat muscles | data.frame | 210 | 4 |
VPA | labstats | Valproic acid (VPA) data set | data.frame | 24 | 5 |
assay.window | labstats | Data to calculate an assay window | data.frame | 40 | 3 |
block.covars | labstats | Data to compare the use of blocking and covariate adjustment | data.frame | 8 | 6 |
cellcount | labstats | Cell count data | data.frame | 9216 | 4 |
festing | labstats | Mouse liver enzyme randomised block design data set | data.frame | 16 | 4 |
fluoxetine | labstats | Fluoxetine data set | data.frame | 20 | 2 |
glycogen | labstats | Glycogen content in rat livers | data.frame | 36 | 4 |
goldstandard | labstats | Data to compare a new method against a gold standard | data.frame | 20 | 5 |
hypertension | labstats | Hypertension repeated measures data | data.frame | 30 | 4 |
locomotor | labstats | Locomotor activity rat data | data.frame | 282 | 4 |
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 | | |
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 | | |
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 | | |
pbmc1 | scAnnotate | pbmc1 | data.frame | 598 | 2001 |
pbmc2 | scAnnotate | pbmc2 | data.frame | 644 | 2001 |
predict_label | scAnnotate | predict_label | character | | |
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 |
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 | | |
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 |
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 |
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 | | |
coverage_res_chr21 | DegNorm | Example CoverageClass data | CoverageClass | | |
res_DegNorm_chr21 | DegNorm | Example DegNormClass data | DegNormClass | | |
EC | GOplot | Transcriptomic information of endothelial cells. | 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 |
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 |
trekfonts | trekfont | Available Star Trek fonts. | character | | |
Acheron | hydrostats | Acheron River flow data | data.frame | 10944 | 2 |
cooper | hydrostats | | data.frame | 7670 | 2 |
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 |
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 |
ex_sales | hpiR | Subset of Seattle Home Sales | data.frame | 5348 | 16 |
seattle_sales | hpiR | Seattle Home Sales | data.frame | 43313 | 16 |
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 |
gobyData | eDNAjoint | gobyData | list | | |
greencrabData | eDNAjoint | greencrabData | list | | |
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 |
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 |
shah1998 | bootf2 | Dissolution data from the article of Shah et al 1998 | list | | |
gap | RGAP | gap data set | list | | |
indicator | RGAP | Indicators fo CUBS | list | | |
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 |
retailsa | rjd3filters | Seasonally Adjusted Retail Sales | list | | |
ts_AR1_Gaussian | imputeFin | | list | | |
ts_AR1_t | imputeFin | | list | | |
ts_VAR_t | imputeFin | | list | | |
countData | SurfR | countData | matrix | 2500 | 4 |
enrichedList | SurfR | enrichedList | list | | |
ind_deg | SurfR | ind_deg | list | | |
metadata | SurfR | metadata | data.frame | 4 | 3 |
rhc_X | optrefine | Right Heart Catheterization Data | matrix | 5735 | 28 |
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 |
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 |
fips_lookup | tpm | FIPS Codes | data.table | 56 | 4 |
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 |
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 |
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 | | |
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 |
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 |
patternsWithFormula | DrugUtilisation | Patterns valid to compute daily dose with the associated formula. | tbl_df | 41 | 9 |
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 | | |
usmacro_growth | bayesianVARs | Data from the US-economy | matrix | 247 | 21 |
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 |
Big5 | jmv | | data.frame | 500 | 5 |
ToothGrowth | jmv | | data.frame | 60 | 3 |
bugs | jmv | | data.frame | 93 | 8 |
iris | jmv | | data.frame | 150 | 5 |
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 |
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 |
exampledates | datefixR | Example dataset of dates in different formats | data.frame | 7 | 3 |
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 |
aboutrsq | datana | About the R-Squared statistics: the Anscombe quartet dataset | data.frame | 11 | 6 |
aboutrsq2 | datana | Sobre el estadístico 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 características biométricas 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 características biométricas 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 árbol 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 árboles de Encino en Portugal | data.frame | 203 | 10 |
crown | datana | Tree crown radii | data.frame | 30 | 10 |
crown2 | datana | Radios de copa de árboles | 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 árboles 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 | Elección 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 árboles 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 árboles 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 | Árboles dentro de parcelas de muestreo en una plantación 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 fertilización | data.frame | 15 | 2 |
ficdiamgr | datana | Diameter growth of trees | data.frame | 35 | 5 |
ficdiamgr2 | datana | Crecimiento diametral de árboles | 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 diámetro 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 árboles en los Estados Unidos | data.frame | 148 | 7 |
idahohd | datana | Tree height-diameter data from Idaho (USA) | data.frame | 372 | 6 |
idahohd2 | datana | Altura-diámetro de árboles 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 árboles de Pinus pinaster en Galicia, España. | data.frame | 85 | 8 |
pinusContorta | datana | Contains spatial location of Pinus contorta trees in sample plots. | data.frame | 2552 | 8 |
pinusContorta2 | datana | Ubicación espacial de árboles 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 árbol 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 | Elección 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 | Ubicación cartesiana de árboles en el bosque de Llancahue | data.frame | 1218 | 5 |
pspRuca | datana | Tree spatial coordinates in the Rucamanque forest | data.frame | 661 | 6 |
pspRuca2 | datana | Ubicación espacial de árboles 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 árbol 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 árboles 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 diámetro y altura de árboles 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 árboles 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 diámetro para árboles 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 árbol 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 árbol en el bosque de Rucamanque | data.frame | 382 | 6 |
formats | pmeasyr | Table des formats | tbl_df | 26618 | 14 |
us_fiscal_ex | bsvars | A 3-variable system of exogenous variables for the US fiscal model for the period 1948 Q1 - 2024 Q1 | mts | 305 | 3 |
us_fiscal_lsuw | bsvars | A 3-variable US fiscal system for the period 1948 Q1 - 2024 Q1 | mts | 305 | 3 |
community_data | forstringr | Data containing whitespaces | tbl_df | 33 | 8 |
richest_in_nigeria | forstringr | Rank of billionaires in Nigeria | tbl_df | 10 | 5 |
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 | | |
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 | | |
monetary | bsvarSIGNs | A 6-variable US monetary policy data, from 1965 Jan to 2007 Aug | mts | 515 | 6 |
optimism | bsvarSIGNs | A 5-variable US business cycle data, from 1955 Q1 to 2004 Q4 | mts | 224 | 5 |
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 | | |
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 | | |
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 | | |
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 |
trendyExampleData | Trendy | Example dataset for Trendy | matrix | 50 | 40 |
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 |
pbmc_small | SeuratObject | A small example version of the PBMC dataset | Seurat | | |
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 | |
KRSA_Mapping_PTK_PamChip_86402_v1 | KRSA | KRSA kinase-substrate mapping file for PamChip 86402 PTK (v1 mapping) | spec_tbl_df | 193 | 2 |
KRSA_Mapping_STK_PamChip_87102_v1 | KRSA | KRSA kinase-substrate mapping file for PamChip 87102 STK (v1 mapping) | spec_tbl_df | 141 | 2 |
KRSA_coverage_PTK_PamChip_86402_v1 | KRSA | KRSA kinase coverage file for PamChip 86402 PTK (v1 mapping) | data.frame | 1278 | 2 |
KRSA_coverage_STK_PamChip_87102_v1 | KRSA | KRSA kinase coverage file for PamChip 87102 STK (v1 mapping) | data.frame | 2423 | 2 |
KRSA_coverage_STK_PamChip_87102_v2 | KRSA | KRSA kinase coverage file for PamChip 87102 STK (v2 mapping, removed PDK kinase) | data.frame | 2422 | 2 |
KRSA_layout_PTK_PamChip_86402_v1 | KRSA | | spec_tbl_df | 204 | 1 |
KRSA_layout_STK_PamChip_87102_v1 | KRSA | | spec_tbl_df | 152 | 1 |
KRSA_uka_mapping_PTK_PamChip_86402_v1 | KRSA | | spec_tbl_df | 1438 | 11 |
KRSA_uka_mapping_STK_PamChip_87102_v1 | KRSA | | spec_tbl_df | 2106 | 11 |
ballModel_edges | KRSA | Protein-Protein Interactions based on PhosphositePlus database | data.frame | 592 | 2 |
ballModel_nodes | KRSA | Protein-Protein Interactions based on PhosphositePlus database | tbl_df | 179 | 2 |
ptk_pamchip_86402_mapping | KRSA | CDRL Complete mapping of peptides to HGNC symbols (PTK PamChip 86402) | tbl_df | 193 | 2 |
stk_pamchip_87102_mapping | KRSA | CDRL Complete mapping of peptides to HGNC symbols (STK PamChip 87102) | tbl_df | 141 | 2 |
. | freealg | Class "dot" | dot | | |
ebirdst_predictor_descriptions | ebirdst | eBird Status and Trends predictors descriptions | tbl_df | 37 | 4 |
ebirdst_predictors | ebirdst | eBird Status and Trends predictor variables | tbl_df | 150 | 4 |
ebirdst_runs | ebirdst | Data frame of species with eBird Status and Trends Data Products | tbl_df | 1118 | 28 |
mozzies_nsw2301 | ggmapinset | Mosquito counts from NSW Arbovirus Surveillance program | tbl_df | 720 | 7 |
snp | abcrf | A simulated example in population genetics | list | | |
snp.obs | abcrf | A simulated example in population genetics | data.frame | 2 | 48 |
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 | | |
four_image_data | littlelisteners | Example data from a Visual World experiment | tbl_df | 20910 | 25 |
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 | | |
unicorn_data | csucistats | Unicorn Data | tbl_df | 750 | 15 |
MICS2014HL | PakPMICS2014HL | Multiple Indicator Cluster Survey (MICS) 2014 Household Listing Questionnaire Data for Punjab, Pakistan | data.table | 246501 | 81 |
cophe_multi_trait_data | cophescan | Simulated multi-trait data | 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 |
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 |
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 | | |
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 |
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 |
d.error | frscore | Simulated data of sixteen cases with measurement error in one case | data.frame | 16 | 5 |
sampleSWCRTLarge | geeCRT | simulated large SW-CRT data | data.frame | 1508 | 10 |
sampleSWCRTSmall | geeCRT | simulated small SW-CRT data | data.frame | 373 | 9 |
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 |
gadarian | stmgui | Gadarian and Albertson data | data.frame | 341 | 4 |
raccoon | sftrack | Movements of two raccoons in an urban park in Florida | data.frame | 445 | 8 |
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 |
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 |
NSCLC | ThresholdROCsurvival | Non-small cell lung cancer (NSCLC) data | data.frame | 203 | 4 |
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 |
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 |
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 |
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 |
sample | sandbox | Example Grain Size Data | data.frame | 1000 | 12 |
sample_osl_aliquots | sandbox | Aliquots Prepared to Measured Virtually | list | | |
PK | guiplot | somedata | data.frame | 26 | 4 |
pc | uklr | UK Postcodes and NUTS3 Codes | spec_tbl_df | 1759911 | 2 |
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 | | |
sbd_bdlim | bdlim | Simulated Birth Data | data.frame | 1000 | 202 |
ABS | rjd3toolkit | | data.frame | 425 | 22 |
Exports | rjd3toolkit | | list | | |
Imports | rjd3toolkit | | list | | |
retail | rjd3toolkit | | list | | |
examples | mri | Examples of Misclassifications of Units | list | | |
CreditMDR | DiSSMod | Credit cards derogatory reports data | data.frame | 13444 | 8 |
DoctorRWM | DiSSMod | German doctor first visits data | data.frame | 7293 | 26 |
pheno | SoyURT | Phenotype | data.frame | 39006 | 13 |
soil | SoyURT | Soil variables | data.frame | 504 | 5 |
weather | SoyURT | Weather variables | data.frame | 74012 | 25 |
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 |
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 |
simsolvd | anoint | Simulated SOLVD-Trial data set | data.frame | 2569 | 13 |
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 | | |
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 | | |
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 |
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 |
pbRNAseq | MultimodalExperiment | MultimodalExperiment Example Data | matrix | 3000 | 1 |
scADTseq | MultimodalExperiment | MultimodalExperiment Example Data | matrix | 8 | 5000 |
scRNAseq | MultimodalExperiment | MultimodalExperiment Example Data | matrix | 3000 | 5000 |
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 |
exon.data | xmapbridge | Sample exon array dataset | data.frame | 8888 | 18 |
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 |
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 |
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 |
duncan | aspect | Duncan dataset | data.frame | 1204 | 12 |
galo | aspect | GALO dataset | data.frame | 1290 | 5 |
wurzer | aspect | Internet terminals | data.frame | 215 | 8 |
riverforest | ccptm | River Forest, IL, Property Tax Data | data.frame | 1208 | 36 |
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 |
fertility | Countr | Fertility data | data.frame | 1243 | 9 |
football | Countr | Football data | data.frame | 3040 | 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 |
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 |
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 |
coal | abctools | Examples of coalescent data | matrix | 100000 | 9 |
coalobs | abctools | Examples of coalescent data | matrix | 100 | 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 |
fish | occumb | Fish eDNA metabarcoding dataset | occumbData | | |
fish_raw | occumb | Fish eDNA metabarcoding dataset | list | | |
gpheats | sport | Heat results of Speedway Grand-Prix | data.frame | 21932 | 11 |
gpsquads | sport | Turnament results of Speedway Grand-Prix | data.frame | 4536 | 9 |
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 |
germancredit | scorecard | German Credit Data | data.frame | 1000 | 21 |
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 |
electricity | ForecastComb | UK Electricity Supply 2007 - 2017 | mts | 123 | 6 |
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 |
lambda | drimmR | lambda genome | SeqFastadna | | |
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 | | |
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 |
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 | |
randomNamesData | randomNames | First names (by gender and ethnicity) and last names (by ethnicity) for randomNames function | environment | | |
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 |
observed | pEPA | Sample Panel of Commodities Spot Prices. | matrix | 303 | 56 |
predicted | pEPA | Sample Panels of Commodities Spot Prices Forecasts. | list | | |
star | evalITR | Tennessee’s Student/Teacher Achievement Ratio (STAR) project | data.frame | 1911 | 14 |
credit_data | SWIM | Credit data set | matrix | 100000 | 7 |
s01 | densityarea | Vowel Space Data | tbl_df | 4245 | 10 |
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 |
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 |
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 | | |
shen_orr_ex | dtangle | Example Subset of Shen-Orr deconvolution data set. | list | | |
goghColors | ggRtsy | Sampling of Colors from Van Gogh Paintings | tbl_df | 986 | 3 |
goghPaintingSets | ggRtsy | Van Gogh Paintings Information | tbl_df | 1931 | 6 |
us_fertilizer_county | usfertilizer | us_fertilizer_county | tbl_df | 625580 | 12 |
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 |
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 |
TwentyNewsgroups | LDAvis | Twenty Newsgroups Data | 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 |
beer | windows.pls | Beer Dataset from Near Infrared Spectroscopy | data.frame | 80 | 577 |
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 |
x3p4c | odetector | Synthetic data set consists of three variables with four clusters | matrix | 130 | 4 |
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 |
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 |
CFAdata | CFAcoop | Colony Formation Assay data on cellular cooperation | data.frame | 454 | 8 |
coral6 | lablaster | Time resolved analysis by laser ablation inductively coupled plasma mass spectrometry of a branching coral, identified hereon as “coral6”. | 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 |
PROSYM | ontoProc | PROSYM: HGNC symbol synonyms for PR (protein ontology) entries identified in Cell Ontology | data.frame | 209947 | 2 |
allGOterms | ontoProc | allGOterms: data.frame with ids and terms | data.frame | 44541 | 2 |
humrna | ontoProc | humrna: a data.frame of SRA metadata related to RNA-seq in humans | data.frame | 513 | 12 |
minicorpus | ontoProc | minicorpus: a vector of annotation strings found in 'study title' of SRA metadata. | character | | |
packDesc2019 | ontoProc | packDesc2019: overview of ontoProc resources | data.frame | 13 | 8 |
packDesc2021 | ontoProc | packDesc2021: overview of ontoProc resources | data.frame | 12 | 6 |
packDesc2022 | ontoProc | packDesc2022: overview of ontoProc resources | data.frame | 14 | 7 |
packDesc2023 | ontoProc | packDesc2023: overview of ontoProc resources | data.frame | 15 | 7 |
stopWords | ontoProc | stopWords: vector of stop words from xpo6.com | character | | |
Cgt | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 2 | 3 |
Fgt | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 2 | 3 |
Mgt | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 2 | 3 |
Rgt | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 2 | 3 |
S1gt | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 2 | 3 |
S2gt | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 2 | 3 |
db | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 11 | 3 |
emperors | KinMixLite | IBD pattern distribution in the Iulius-Claudius pedigree | IBD | | |
epg | KinMixLite | Small data set for demonstrating some capabilities of KinMix and KinMixLite | data.frame | 9 | 3 |
andy2011params | pRoloc | Class '"AnnotationParams"' | AnnotationParams | | |
dunkley2006params | pRoloc | Class '"AnnotationParams"' | AnnotationParams | | |
GlobalPatterns | mia | Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. | TreeSummarizedExperiment | | |
HintikkaXOData | mia | Multiomics dataset from 40 rat samples | MultiAssayExperiment | | |
Tengeler2020 | mia | Gut microbiota profiles of 27 individuals with ADHD and healthy controls | TreeSummarizedExperiment | | |
Tito2024QMP | mia | Fecal microbiota samples from 589 patients across different colorectal cancer stages | TreeSummarizedExperiment | | |
dmn_se | mia | Twins' microbiome data from 278 individuals | SummarizedExperiment | | |
enterotype | mia | Human gut microbiome dataset from 22 subjects based on shotgun DNA sequencing | TreeSummarizedExperiment | | |
esophagus | mia | Human esophageal community from 3 individuals | TreeSummarizedExperiment | | |
peerj13075 | mia | Skin microbial profiles 58 genetically unrelated individuals | TreeSummarizedExperiment | | |
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 |
alignment_vals | ggalignment | Alignment Values | data.frame | 9 | 1 |
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 |
big5 | frequency | Big 5 Personality Factors Survey Data | data.frame | 15735 | 56 |
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 |
MetsaKasvVyoh | efdm | Finnish bio-geographical regions | sf | 298 | 2 |
example | efdm | Example dataset. | 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 |
King200Breast | SwimmeR | Results for Lilly King's 200 Breaststrokes | spec_tbl_df | 50 | 4 |
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 |
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 |
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 |
xymap | PROJ | xymap data for testing | matrix | 5494 | 2 |
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 |
heart_disease | cheese | Heart Disease | tbl_df | 303 | 9 |
state_boundaries_wgs84 | USA.state.boundaries | state_boundaries_wgs84 with sf read data | sf | 61 | 14 |
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 |
dat.metap | metap | Example data | list | | |
bin_ranges | checkLuhn | BIN ranges | tbl_df | 48 | 5 |
ICAapp | ccmEstimator | Application data | data.frame | 1602 | 14 |
ttrc | TTR | Technical Trading Rule Composite data | data.frame | 5550 | 6 |
df_hospitals_ortho | mactivate | Orthopedic Device Sales | data.frame | 4703 | 15 |
breastcancer | OneR | Breast Cancer Wisconsin Original Data Set | data.frame | 699 | 10 |
Tourism | wINEQ | Sample survey on trips | tbl_df | 5319 | 17 |
Well_being | wINEQ | Sample survey on quality of life | tbl_df | 1197 | 27 |
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 | | |
col_graph | miaViz | miaViz example data | tbl_graph | | |
row_graph | miaViz | miaViz example data | tbl_graph | | |
row_graph_order | miaViz | miaViz example data | tbl_graph | | |
Koren.16S | mixOmics | 16S microbiome atherosclerosis study | list | | |
breast.TCGA | mixOmics | Breast Cancer multi omics data from TCGA | list | | |
breast.tumors | mixOmics | Human Breast Tumors Data | list | | |
diverse.16S | mixOmics | 16S microbiome data: most diverse bodysites from HMP | list | | |
linnerud | mixOmics | Linnerud Dataset | list | | |
liver.toxicity | mixOmics | Liver Toxicity Data | list | | |
multidrug | mixOmics | Multidrug Resistence Data | list | | |
nutrimouse | mixOmics | Nutrimouse Dataset | list | | |
srbct | mixOmics | Small version of the small round blue cell tumors of childhood data | list | | |
stemcells | mixOmics | Human Stem Cells Data | list | | |
vac18 | mixOmics | Vaccine study Data | list | | |
vac18.simulated | mixOmics | Simulated data based on the vac18 study for multilevel analysis | list | | |
yeast | mixOmics | Yeast metabolomic study | list | | |
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 |
greta_deps_tf_tfp | greta | Suggested valid Python dependencies for greta | tbl_df | 63 | 5 |
trim32 | abess | The Bardet-Biedl syndrome Gene expression data | data.frame | 120 | 501 |
pedigree | SeqVarTools | Pedigree for example data | data.frame | 90 | 6 |
FCWB.demo | nat.templatebrains | Sample template brain: FlyCircuit Whole Brain | templatebrain | | |
UKgrid | UKgrid | The UK National Electricity Transmission System Dataset | data.frame | 254592 | 9 |
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 |
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 |
atex2b | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
atex4 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
atex5 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
benchmark_1 | OncoSimulR | Summary results from some benchmarks reported in the vignette. | data.frame | 16 | 39 |
benchmark_1_0.05 | OncoSimulR | Summary results from some benchmarks reported in the vignette. | data.frame | 16 | 39 |
benchmark_2 | OncoSimulR | Summary results from some benchmarks reported in the vignette. | data.frame | 14 | 38 |
benchmark_3 | OncoSimulR | Summary results from some benchmarks reported in the vignette. | data.frame | 14 | 38 |
ex_missing_drivers_b11 | OncoSimulR | An example where there are intermediate missing drivers. | oncosimul | | |
ex_missing_drivers_b12 | OncoSimulR | An example where there are intermediate missing drivers. | oncosimul | | |
examplePosets | OncoSimulR | Example posets | list | | |
examplesFitnessEffects | OncoSimulR | Examples of fitness effects | list | | |
mcfLs | OncoSimulR | mcfLs simulation from the vignette | oncosimul | | |
osi | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
osi_with_ints | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
s_3_a | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
s_3_b | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
simT2 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
simT3 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
simul_period_1 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
smyelo3v57 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
uvex2 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
uvex3 | OncoSimulR | Runs from simulations of interventions examples shown in the vignette. Most, but not all, are from intervention examples. | oncosimul | | |
woAntibS | OncoSimulR | Runs from simulations of frequency-dependent examples shown in the vignette. | oncosimul | | |
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 |
riskcor | SEset | Cognitive risk sample correlation matrix | matrix | 6 | 6 |
exampleDESeqResults | pathlinkR | List of example results from DESeq2 | list | | |
groupedPathwayColours | pathlinkR | Colour assignments for grouped pathways | character | | |
hallmarkDatabase | pathlinkR | Table of Hallmark gene sets and their genes | tbl_df | 8209 | 2 |
innateDbPPI | pathlinkR | InnateDB PPI data | tbl_df | 152256 | 2 |
keggDatabase | pathlinkR | Table of KEGG pathways and genes | tbl_df | 32883 | 4 |
mappingFile | pathlinkR | Table of human gene ID mappings | tbl_df | 43993 | 3 |
pathwayCategories | pathlinkR | Top-level pathway categories | tbl_df | 3326 | 5 |
reactomeDatabase | pathlinkR | Table of all Reactome pathways and genes | tbl_df | 123574 | 3 |
sigoraDatabase | pathlinkR | Table of all Sigora pathways and their constituent genes | tbl_df | 60775 | 4 |
sigoraExamples | pathlinkR | Sigora enrichment example | tbl_df | 66 | 12 |
VSGFS | DoE.base | VSGFS: an experiment using an optimized orthogonal array in 72 runs | design | 72 | 10 |
APAP | pksensi | Pharmacokinetic Dataset of Acetaminophen | data.frame | 32 | 7 |
iBAQ | CoFRA | data frame containing iBAQ values | data.frame | 18889 | 33 |
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 |
dtClimate | ggTimeSeries | Climate data. | data.table | 23628 | 5 |
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 |
unemp | mFilter | US Quarterly Unemployment Series | ts | | |
coords | sgstar | Coordinate of region in South Sumatera | matrix | 17 | 2 |
simulatedata | sgstar | Sample Data for simulate analysis data | data.frame | 100 | 17 |
RothC_C0_ex | sorcering | Initial Soil Organic Carbon Data for RothC | numeric | | |
RothC_Cin_ex | sorcering | Carbon Input Data for RothC | matrix | 60 | 5 |
RothC_Cin_ex_sl | sorcering | Carbon Input Data for RothC using multiple sites | list | | |
RothC_Cin_ex_sl_spin | sorcering | Carbon Input Data for RothC using multiple sites with spinup run | list | | |
RothC_N0_ex | sorcering | Initial Soil Organic Nitrogen Data for RothC | numeric | | |
RothC_Nin_ex | sorcering | Nitrogen Input Data for RothC | matrix | 60 | 5 |
RothC_Nin_ex_sl | sorcering | Nitrogen Input Data for RothC using multiple sites | list | | |
RothC_Nin_ex_sl_spin | sorcering | Nitrogen Input Data for RothC using multiple sites with spinup run | list | | |
RothC_env_in_ex | sorcering | Environmental Input Data for RothC | matrix | 60 | |
RothC_site_ex | sorcering | Environmental Input Data for RothC | numeric | | |
RothC_xi_ex | sorcering | Environmental Factors Data for RothC | matrix | 60 | 5 |
Yasso_C0_ex_sl | sorcering | Initial Soil Organic Carbon Data for Yasso using Multiple Sites | list | | |
Yasso_Cin_ex_wood_u_sl | sorcering | Carbon Input Data for Yasso using Multiple Sites | list | | |
Yasso_N0_ex_sl | sorcering | Initial Soil Organic Nitrogen Data for Yasso using Multiple Sites | list | | |
Yasso_Nin_ex_wood_u_sl | sorcering | Nitrogen Input Data for Yasso using Multiple Sites | list | | |
meas_data_ex | sorcering | Measured Data Input | matrix | 3 | |
indonRespir | gammSlice | Eespiratory infection in Indonesian children | data.frame | 1200 | 12 |
toenail | gammSlice | Toenail infection clinical trial | data.frame | 1908 | 5 |
minnbreast | Pedixplorer | Minnesota Breast Cancer Study | data.frame | 28081 | 15 |
relped | Pedixplorer | Relped data | data.frame | 8 | 4 |
sampleped | Pedixplorer | Sampleped data | data.frame | 55 | 8 |
indexes | PortfolioAnalytics | Six Major Economic Indexes | xts | 360 | 6 |
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 |
countrycode | learningtower | Country iso3c and name mapping for PISA OECD countries participants. | spec_tbl_df | 109 | 2 |
school | learningtower | School data available for the years 2000-2018 from the PISA OECD database | tbl_df | 109756 | 13 |
student_subset_2000 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 2150 | 22 |
student_subset_2003 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 2050 | 22 |
student_subset_2006 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 2850 | 22 |
student_subset_2009 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 3700 | 22 |
student_subset_2012 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 3250 | 22 |
student_subset_2015 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 3650 | 22 |
student_subset_2018 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 4000 | 22 |
student_subset_2022 | learningtower | Sample student data available for the years 2000-2018 from the PISA OECD database | tbl_df | 4000 | 23 |
sampleData1 | odkr | Sample dataset from an impact evaluation study of a mother and child nutrition programme in Kassala State, Sudan. This dataset contains cluster level data from the survey. | data.frame | 50 | 16 |
sampleData2 | odkr | Sample dataset from an impact evaluation study of a mother and child nutrition programme in Kassala State, Sudan. This dataset contains information from mother respondents. | data.frame | 50 | 16 |
sampleData3 | odkr | Sample dataset from an impact evaluation study of a mother and child nutrition programme in Kassala State, Sudan. This dataset contains information from child respondents. | data.frame | 50 | 9 |
electricity | nixtlar | Electricity dataset | data.frame | 8400 | 3 |
electricity_exo_vars | nixtlar | Electricity dataset with exogenous variables | data.frame | 8400 | 12 |
electricity_future_exo_vars | nixtlar | Future values for the electricity dataset with exogenous variables | data.frame | 120 | 11 |
cmip6 | quadmesh | CMIP6 sample | RasterBrick | | |
etopo | quadmesh | World topography map | RasterLayer | | |
worldll | quadmesh | World raster map | RasterLayer | | |
xymap | quadmesh | World map | matrix | 82403 | 2 |
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 | | |
karate | einet | Zachary's karate club | igraph | | |
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 | | |
siccodes | finreportr | Standard Industrial Classification Code List | data.frame | 444 | 2 |
statecodes | finreportr | EDGAR State and Country Codes | data.frame | 310 | 2 |
data.adjacent.mat | AST | data frame of adjacent provinces in Iran | matrix | 31 | |
data.residual.AST | AST | residual data set | data.frame | 3000 | 6 |
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 |
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 |
economo | ggsegEconomo | economo atlas | brain_atlas | | |
economo_3d | ggsegEconomo | economo atlas | ggseg3d_atlas | 4 | 4 |
star | BET | Coordinates of Brightest Stars in the Night Sky | data.frame | 256 | 2 |
Y | NBtsVarSel | Observation matrix Y | numeric | | |
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 |
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 | | |
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 | | |
data.sim | CRTgeeDR | The data.sim Dataset. | data.frame | 10000 | 11 |
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 |
Data_saekernel | saekernel | Sample Data for Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel | data.frame | 100 | 3 |
cereb | BCgee | Cerebrovascular Deficiency | data.frame | 134 | 4 |
seizure | BCgee | Epiliptic Seizures | data.frame | 59 | 7 |
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 |
pixar_films | headliner | This data comes from 'pixarfilms' package by Eric Leung (2022) | tbl_df | 22 | 10 |
painbow_data | painbow | A 2D heatmap from XKCD's painbow comic | tbl_df | 58425 | 3 |
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 | | |
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 |
SimData | eyeRead | A simulated dataset with eye tracking data | data.frame | 37 | 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 |
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 | | |
AEdemand | thief | Accident and Emergency demand in the UK | mts | 240 | 13 |
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 |
QuadRules | mvQuad | nodes and weights for 1D - Gauss-Quadrature | list | | |
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 |
topcolour.ig.vancouver.2014 | ig.vancouver.2014.topcolour | Instagram 2014 Vancouver dataset top colour | data.frame | 245736 | 2 |
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 |
testdata | RPscoring | Test Dataset | matrix | 8 | |
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 |
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 | | |
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 |
simdata | sureLDA | Simulated Dataset | list | | |
LeMis | threejs | Les Miserables Character Coappearance Data | igraph | | |
ego | threejs | Facebook social circles | igraph | | |
ecc_plaque | ADAPT | Plaque samples from early childhood dental caries studies | phyloseq | | |
ecc_saliva | ADAPT | Saliva samples from early childhood dental caries studies | phyloseq | | |
Conesprings | NetIndices | Cone Spring ecosystem. | matrix | 7 | 6 |
Takapoto | NetIndices | Takapoto atoll planktonic food web | matrix | 8 | 10 |
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 |
beissinger_data | ohtadstats | Chicken Genotype Data | matrix | 1417 | 100 |
miyashita_langley_data | ohtadstats | Drosophila melanogaster genotypes | matrix | 64 | 85 |
gcdata | germinationmetrics | Germination count data | data.frame | 15 | 17 |
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 |
test | CutpointsOEHR | A simulation data to test cutpointsOEHR | data.frame | 200 | 4 |
US30 | ROI | Monthly return data for 30 of the largest US stocks | matrix | 180 | 30 |
nih_sample_data | nih.joinpoint | Sample dataset | tbl_df | 105 | 4 |
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 | | |
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 | | |
BanxicoCatalog | banxicoR | Catalog of some ID's | data.frame | 133 | 9 |
toy | akiFlagger | Toy dataset | data.table | 1078 | 6 |
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 | | |
corn_data | maize | Synthetic Corn Dataset for Corny Example | tbl_df | 300 | 3 |
Germany | gamlss2 | Map of Germany | sf | 403 | 4 |
HarzTraffic | gamlss2 | Traffic Counts at Sonnenberg in the Harz Region | data.frame | 1057 | 16 |
storms | gamlss2 | Severe Storms in Germany | data.frame | 3494 | 8 |
ROSETTA.centroids | aqp | Average Hydraulic Parameters from the ROSETTA Model by USDA Soil Texture Class | data.frame | 12 | 13 |
SPC.with.overlap | aqp | Example SoilProfileCollection with Overlapping Horizons | SoilProfileCollection | | |
ca630 | aqp | Soil Data from the Central Sierra Nevada Region of California | list | | |
equivalent_munsell | aqp | Indices of "equivalent" Munsell chips in the 'munsell' data set | list | | |
jacobs2000 | aqp | Soil Morphologic Data from Jacobs et al. 2002. | SoilProfileCollection | | |
munsell | aqp | Munsell to sRGB Lookup Table for Common Soil Colors | data.frame | 10447 | 9 |
munsell.spectra | aqp | Spectral Library of Munsell Colors | data.frame | 136584 | 6 |
munsell.spectra.wide | aqp | Spectral Library of Munsell Colors | data.frame | 36 | 3795 |
munsellHuePosition | aqp | Munsell Hue Position Reference | data.frame | 41 | 4 |
osd | aqp | Example Output from soilDB::fetchOSD() | SoilProfileCollection | | |
reactionclass | aqp | pH Reaction Classes | data.frame | 11 | 3 |
rowley2019 | aqp | Soil Morphologic, Geochemical, and Mineralogy Data from Rowley et al. 2019. | SoilProfileCollection | | |
sierraTransect | aqp | Soil Physical and Chemical Data Related to Studies in the Sierra Nevada Mountains, CA, USA. | SoilProfileCollection | | |
soil_minerals | aqp | Munsell Colors of Common Soil Minerals | data.frame | 20 | 5 |
soiltexture | aqp | Lookup tables for sand, silt, clay, texture class, and textural modifiers. | list | | |
sp1 | aqp | Soil Profile Data Example 1 | data.frame | 60 | 18 |
sp2 | aqp | Honcut Creek Soil Profile Data | data.frame | 154 | 22 |
sp3 | aqp | Soil Profile Data Example 3 | data.frame | 46 | 17 |
sp4 | aqp | Soil Chemical Data from Serpentinitic Soils of California | data.frame | 30 | 13 |
sp5 | aqp | Sample Soil Database #5 | SoilProfileCollection | | |
sp6 | aqp | Soil Physical and Chemical Data from Manganiferous Soils | data.frame | 64 | 14 |
spectral.reference | aqp | Standard Illuminants and Observers | data.frame | 71 | 9 |
traditionalColorNames | aqp | Traditional Soil Color Names | data.frame | 482 | 2 |
us.state.soils | aqp | US State Soils | data.frame | 52 | 3 |
wilson2022 | aqp | Example Data from Wilson et al. 2022 | SoilProfileCollection | | |
blog.data | packageRank | Blog post data. | list | | |
rstudio.logs | packageRank | Eight RStudio Download Logs to Fix Duplicate Logs Errors in 'cranlogs'. | list | | |
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 |
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 | | |
coffee | PriceIndices | A real data set on sold coffee | data.frame | 42561 | 6 |
dataAGGR | PriceIndices | A small artificial scanner data set for a demonstration of data aggregation | data.frame | 9 | 6 |
dataCOICOP | PriceIndices | A real scanner data set for the product classification | data.frame | 139600 | 10 |
dataMATCH | PriceIndices | An artificial scanner data set for product matching | data.frame | 30 | 7 |
dataU | PriceIndices | An artificial, small scanner data set | data.frame | 6 | 5 |
data_DOWN_UP_SIZED | PriceIndices | An artificial data set on sold coffee | data.frame | 51 | 6 |
milk | PriceIndices | A real data set on sold milk | data.frame | 4386 | 6 |
sugar | PriceIndices | A real data set on sold sugar | data.frame | 7666 | 6 |
ads | dst | The Captain's Problem. 'ads': Relation between variables Arrival (A), Departure delay (D) and Sailing delay (S) | matrix | 18 | 17 |
captain_result | dst | The Captain's Problem. 'swr': Result of the evaluation of the Hypergraph at node Arrival (A) | list | | |
dlfm | dst | The Captain's Problem. 'dlfm': Relation between variables Departure delay (D), Loading delay (L), Forecast of the weather (F), Maintenance delay (M) | data.frame | 10 | 12 |
fw | dst | The Captain's Problem. 'fw': Relation between variables Forecast of the weather (F) and Weather at sea (W) | matrix | 4 | 6 |
mrf | dst | The Captain's Problem. 'mrf': Relation between variables No Maintenance (M = false) and Repairs at sea (R) | matrix | 8 | 6 |
mrt | dst | The Captain's Problem. 'mrt': Relation between variables Maintenance done (M = true) and Repairs at sea (R) | matrix | 8 | 6 |
swr | dst | The Captain's Problem. 'swr': Relation between variables Sailing delay (S), Weather at sea (W), and Repairs at sea (R) | matrix | 6 | 10 |
part_bfi | latent2likert | Agreeableness and Gender Data | data.frame | 2800 | 6 |
BiopsyTrees | dowser | Example Ig lineage trees with biopsy reconstructions. | tbl_df | 8 | 5 |
ExampleAirr | dowser | Example AIRR database | tbl_df | 389 | 30 |
ExampleClones | dowser | Example Ig lineage trees | tbl_df | 89 | 5 |
ExampleDbChangeo | dowser | Example Change-O database | tbl_df | 2000 | 15 |
ExampleMixedClones | dowser | Example Multiple Partition Trees | tbl_df | 4 | 6 |
ExampleMixedDb | dowser | Example Change-O database | tbl_df | 38 | 56 |
IsotypeTrees | dowser | Example Ig lineage trees with isotype reconstructions. | tbl_df | 34 | 5 |
TimeTrees | dowser | Example Ig lineage trees sampled over time. | tbl_df | 6 | 12 |
twigs | rTwig | Twig Database | tbl_df | 104 | 7 |
additional.residency.results | actel | Example residency results | list | | |
example.results | actel | Example migration results | list | | |
claims_transactional | lossrx | claims_transactional | tbl_df | 80278 | 12 |
exposures | lossrx | exposures | tbl_df | 855 | 5 |
losses | lossrx | losses | tbl_df | 79748 | 30 |
allMethods | dtComb | Includes machine learning models used for the mlComb function | data.frame | 113 | 2 |
exampleData1 | dtComb | Examples data for the dtComb package | data.frame | 225 | 3 |
exampleData2 | dtComb | A data set containing the carriers of a rare genetic disorder for 120 samples. | data.frame | 120 | 5 |
exampleData3 | dtComb | A simulation data containing 250 diseased and 250 healthy individuals. | data.frame | 500 | 3 |
paramsMWR | MassWateR | Master parameter list and units for Characteristic Name column in results data | tbl_df | 46 | 4 |
thresholdMWR | MassWateR | Master thresholds list for analysis of results data | tbl_df | 28 | 10 |
ASVAB | mirt | Description of ASVAB data | data.frame | 16 | 8 |
Bock1997 | mirt | Description of Bock 1997 data | data.frame | 64 | 4 |
LSAT6 | mirt | Description of LSAT6 data | data.frame | 30 | 6 |
LSAT7 | mirt | Description of LSAT7 data | data.frame | 32 | 6 |
SAT12 | mirt | Description of SAT12 data | data.frame | 600 | 32 |
SLF | mirt | Social Life Feelings Data | data.frame | 32 | 6 |
Science | mirt | Description of Science data | data.frame | 392 | 4 |
deAyala | mirt | Description of deAyala data | matrix | 32 | 6 |
aegypti | ripserr | _Aedes aegypti_ occurrences in Brazil in 2013 | tbl_df | 4411 | 10 |
case_predictors | ripserr | State-level predictors of mosquito-borne illness in Brazil | data.frame | 27 | 4 |
leslie_mpm1 | Rage | Example Leslie matrix population model (MPM) | list | | |
mpm1 | Rage | Example matrix population model (MPM) | list | | |
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 |
GSM | secr | Black Bear Hair Snag Dataset | sfc_POLYGON | | |
LStraps | secr | Skink Pitfall Data | traps | 462 | 2 |
OVpossumCH | secr | Orongorongo Valley Brushtail Possums | capthist | | |
blackbear.0 | secr | Black Bear Hair Snag Dataset | secr | | |
blackbear.h2bk | secr | Black Bear Hair Snag Dataset | secr | | |
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 |
lcademo | MplusAutomation | Latent Class Analysis Demonstration | list | | |
Sa | chromatographR | Raw goldenrod root chromatograms | list | | |
Sa_pr | chromatographR | Preprocessed goldenrod root chromatograms | list | | |
Sa_warp | chromatographR | Warped goldenrod root chromatograms. | list | | |
pk_tab | chromatographR | Goldenrod peak table | peak_table | | |
bbs_data_sample | bbsBayes2 | Sample BBS data | list | | |
bbs_models | bbsBayes2 | Stan models included in bbsBayes2 | tbl_df | 9 | 3 |
bbs_strata | bbsBayes2 | List of included strata | list | | |
equal_area_crs | bbsBayes2 | equal_area_crs | crs | | |
pacific_wren_model | bbsBayes2 | Example model output | list | | |
species_forms | bbsBayes2 | Species forms | data.frame | 14 | 5 |
species_notes | bbsBayes2 | Species notes | data.frame | 6 | 5 |
namcs2019sv | surveytable | Selected variables from the National Ambulatory Medical Care Survey (NAMCS) 2019 Public Use File (PUF) | survey.design2 | | |
namcs2019sv_df | surveytable | Selected variables from the National Ambulatory Medical Care Survey (NAMCS) 2019 Public Use File (PUF) | data.frame | 8250 | 33 |
rccsu2018 | surveytable | National Study of Long-Term Care Providers (NSLTCP) Residential Care Community (RCC) Services User (SU) 2018 Public Use File (PUF) | survey.design2 | | |
uspop2019 | surveytable | US Population in 2019 | list | | |
safo | flowchart | Random generated dataset from the SAFO study | tbl_df | 925 | 21 |
COVID19 | HDNRA | HDNRA_data COVID19 | matrix | 87 | |
corneal | HDNRA | HDNRA_data corneal | matrix | 150 | 2000 |
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 |
mthd_list_defaults | tcpl | Lists of data frames returned from tcplMthdList invitrodb v4.2 | list | | |
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 | | |
ae | pharmaversesdtm | Adverse Events | tbl_df | 1191 | 35 |
ae_ophtha | pharmaversesdtm | Adverse Events for Ophthalmology | tbl_df | 1191 | 36 |
ce_vaccine | pharmaversesdtm | Clinical Events for Vaccine | tbl_df | 44 | 29 |
cm | pharmaversesdtm | Concomitant Medication | tbl_df | 7510 | 21 |
dm | pharmaversesdtm | Demography | tbl_df | 306 | 25 |
dm_peds | pharmaversesdtm | Demographic Dataset-pediatrics | tbl_df | 5 | 26 |
dm_vaccine | pharmaversesdtm | Demographics for Vaccine | tbl_df | 2 | 28 |
ds | pharmaversesdtm | Disposition | tbl_df | 850 | 13 |
eg | pharmaversesdtm | Electrocardiogram | tbl_df | 26717 | 23 |
ex | pharmaversesdtm | Exposure | tbl_df | 591 | 17 |
ex_ophtha | pharmaversesdtm | Exposure for Ophthalmology | tbl_df | 591 | 19 |
ex_vaccine | pharmaversesdtm | Exposures for Vaccine | tbl_df | 4 | 21 |
face_vaccine | pharmaversesdtm | Findings About Clinical Events for Vaccine | tbl_df | 307 | 30 |
is_vaccine | pharmaversesdtm | Immunogenicity Specimen Assessments for Vaccine | tbl_df | 16 | 24 |
lb | pharmaversesdtm | Laboratory Measurements | tbl_df | 59580 | 23 |
mh | pharmaversesdtm | Medical History | tbl_df | 1818 | 28 |
oe_ophtha | pharmaversesdtm | Ophthalmic Examinations for Ophthalmology | grouped_df | 15344 | 25 |
pc | pharmaversesdtm | Pharmacokinetic Concentrations | tbl_df | 4572 | 20 |
pp | pharmaversesdtm | Pharmacokinetic Parameters | data.frame | 2688 | 14 |
qs_ophtha | pharmaversesdtm | Questionnaire for Ophthalmology | tbl_df | 75922 | 20 |
rs_onco | pharmaversesdtm | Disease Response for Oncology | tbl_df | 5808 | 19 |
rs_onco_imwg | pharmaversesdtm | Disease Response (IMWG) | tbl_df | 65 | 17 |
rs_onco_irecist | pharmaversesdtm | Disease Response (iRECIST) for Oncology | tbl_df | 376 | 19 |
rs_onco_recist | pharmaversesdtm | Disease Response (RECIST 1.1) for Oncology | tbl_df | 66 | 14 |
sc_ophtha | pharmaversesdtm | Subject Characteristic for Ophthalmology | tbl_df | 254 | 12 |
sdg_db | pharmaversesdtm | SDG | tbl_df | 16 | 5 |
smq_db | pharmaversesdtm | Standardized MedDRA Queries | tbl_df | 44 | 6 |
suppae | pharmaversesdtm | Supplemental Adverse Events | tbl_df | 1191 | 10 |
suppce_vaccine | pharmaversesdtm | Supplemental Qualifiers for Clinical Events for Vaccine | tbl_df | 4 | 9 |
suppdm | pharmaversesdtm | Supplemental Demography | tbl_df | 1197 | 10 |
suppdm_vaccine | pharmaversesdtm | Supplemental Qualifiers for Demographics for Vaccine | tbl_df | 2 | 9 |
suppds | pharmaversesdtm | Supplemental Disposition | tbl_df | 3 | 9 |
suppex_vaccine | pharmaversesdtm | Supplemental Qualifiers for Exposures for Vaccine | tbl_df | 4 | 9 |
suppface_vaccine | pharmaversesdtm | Supplemental Qualifiers for Findings About for Clinical Events for Vaccine | tbl_df | 4 | 9 |
suppis_vaccine | pharmaversesdtm | Supplemental Qualifiers for Immunogenicity Specimen Assessments for Vaccine | tbl_df | 16 | 10 |
supprs_onco_imwg | pharmaversesdtm | Supplemental Qualifiers for RS_ONCO_IMWG | tbl_df | 19 | 9 |
supptr_onco | pharmaversesdtm | Supplemental Tumor Results for Oncology | tbl_df | 55995 | 9 |
sv | pharmaversesdtm | Subject Visits | tbl_df | 3559 | 8 |
tr_onco | pharmaversesdtm | Tumor Results for Oncology | tbl_df | 55995 | 24 |
tr_onco_recist | pharmaversesdtm | Tumor Results (RECIST 1.1) for Oncology | tbl_df | 546 | 19 |
ts | pharmaversesdtm | Trial Design | tbl_df | 33 | 6 |
tu_onco | pharmaversesdtm | Tumor Identification for Oncology | tbl_df | 7734 | 18 |
tu_onco_recist | pharmaversesdtm | Tumor Identification (RECIST 1.1) for Oncology | tbl_df | 75 | 16 |
vs | pharmaversesdtm | Vital Signs | tbl_df | 29643 | 24 |
vs_peds | pharmaversesdtm | Vital signs Dataset-pediatrics | tbl_df | 164 | 26 |
vs_vaccine | pharmaversesdtm | Vital Signs for Vaccine | grouped_df | 28 | 23 |
concept_abbrev | openalexR | Concepts and abbreviations. | tbl_df | 20 | 3 |
countrycode | openalexR | Index of Countries and their alpha-2 and aplha-3 codes. | data.frame | 250 | 3 |
metadata_forestdata | forestdata | Metadata for 'forestdata' functions | list | | |
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 |
L7_ETMs | stars | Landsat-7 bands for a selected region around Olinda, BR | stars_proxy | | |
bcsd_obs | stars | Monthly Gridded Meteorological Observations | stars_proxy | | |
stars_sentinel2 | stars | Sentinel-2 sample tile | stars_proxy | | |
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 |
baxter_clinical | partition | Microbiome data | tbl_df | 172 | 8 |
baxter_data_dictionary | partition | Microbiome data | tbl_df | 1351 | 3 |
baxter_family | partition | Microbiome data | tbl_df | 172 | 35 |
baxter_genus | partition | Microbiome data | tbl_df | 172 | 82 |
baxter_otu | partition | Microbiome data | tbl_df | 172 | 1234 |
MTPL | insurancerating | Characteristics of 30,000 policyholders in a Motor Third Party Liability (MTPL) portfolio. | tbl_df | 30000 | 7 |
MTPL2 | insurancerating | Characteristics of 3,000 policyholders in a Motor Third Party Liability (MTPL) portfolio. | tbl_df | 3000 | 6 |
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 | | |
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 | | |
epireview_core_cols | epiparameter | A vector of 'character' strings with the core column names of the epidemiological parameter data exported by the 'epireview' R package. | character | | |
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 | | |
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 |
ChromHMMiterations | animint2 | ChromHMM iterations | list | | |
FluView | animint2 | FluView | list | | |
FunctionalPruning | animint2 | Functional Pruning Algorithm | list | | |
PeakConsistency | animint2 | Consistency of segmentation models in simulated Poisson peaks | list | | |
TestROC | animint2 | Test ROC curves | list | | |
UStornadoes | animint2 | Tornadoes in the United States from 1950 to 2012 | data.frame | 41620 | 32 |
VariantModels | animint2 | Error rates of supervised learning methods for variant calling | list | | |
WorldBank | animint2 | Demographics by country from 1960 to 2012 | data.frame | 11342 | 15 |
breakpoints | animint2 | The breakpointError of simulated signals | list | | |
change | animint2 | Graphical model structure change | list | | |
climate | animint2 | Climate data in central America from 1995 to 2000 | data.frame | 41472 | 16 |
compare | animint2 | Testing rank and compare SVM on simulated patterns | list | | |
diamonds | animint2 | Prices of 50,000 round cut diamonds | tbl_df | 53940 | 10 |
economics | animint2 | US economic time series. | tbl_df | 574 | 6 |
economics_long | animint2 | US economic time series. | data.frame | 2870 | 4 |
faithfuld | animint2 | 2d density estimate of Old Faithful data | tbl_df | 5625 | 3 |
generation.loci | animint2 | Evolution simulation | data.frame | 120000 | 6 |
intreg | animint2 | Interval regression | list | | |
luv_colours | animint2 | 'colors()' in Luv space. | data.frame | 657 | 4 |
malaria | animint2 | Malaria parasite genome variants | list | | |
midwest | animint2 | Midwest demographics. | tbl_df | 437 | 28 |
mixtureKNN | animint2 | K-Nearest-Neighbors model of the mixture example data | list | | |
montreal.bikes | animint2 | Montreal bikes | list | | |
mpg | animint2 | Fuel economy data from 1999 and 2008 for 38 popular models of car | tbl_df | 234 | 11 |
msleep | animint2 | An updated and expanded version of the mammals sleep dataset. | tbl_df | 83 | 11 |
pirates | animint2 | Worldwide pirate attacks from 1978 to 2013 | data.frame | 6636 | 14 |
presidential | animint2 | Terms of 11 presidents from Eisenhower to Obama. | tbl_df | 11 | 4 |
prior | animint2 | Class prior change | list | | |
prostateLasso | animint2 | Lasso model of the prostate cancer data set | list | | |
seals | animint2 | Vector field of seal movements. | tbl_df | 1155 | 4 |
txhousing | animint2 | Housing sales in TX. | tbl_df | 8602 | 9 |
vervet | animint2 | Vervet monkey intestinal microbiome | list | | |
worldPop | animint2 | World population by subcontinent | data.frame | 294 | 4 |
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 |
pftmapping | PEcAn.ED2 | Mapping of PEcAn PFT names to ED2 PFT numbers | data.frame | 73 | 2 |
sibcasa_output_vars | PEcAn.SIBCASA | Output variables for SIBCASA | data.frame | 131 | 6 |
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 |
physeq | microbial | The physeq data was modified from the (Data) Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample (2011) | phyloseq | | |
co2.1850.2020 | PEcAn.LPJGUESS | | data.frame | 171 | 2 |
ex1_delayed_effect | simtrial | Time-to-event data example 1 for non-proportional hazards working group | tbl_df | 361 | 4 |
ex2_delayed_effect | simtrial | Time-to-event data example 2 for non-proportional hazards working group | tbl_df | 272 | 4 |
ex3_cure_with_ph | simtrial | Time-to-event data example 3 for non-proportional hazards working group | tbl_df | 280 | 4 |
ex4_belly | simtrial | Time-to-event data example 4 for non-proportional hazards working group | tbl_df | 774 | 4 |
ex5_widening | simtrial | Time-to-event data example 5 for non-proportional hazards working group | tbl_df | 165 | 4 |
ex6_crossing | simtrial | Time-to-event data example 6 for non-proportional hazards working group | tbl_df | 290 | 4 |
mb_delayed_effect | simtrial | Simulated survival dataset with delayed treatment effect | data.frame | 200 | 4 |
standard_vars | PEcAn.utils | Standardized variable names and units for PEcAn | data.frame | 117 | 12 |
trait.dictionary | PEcAn.utils | | data.frame | 101 | 4 |
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 |
csafe | handwriter | Cursive written word: csafe | matrix | 111 | |
example_analysis | handwriter | Example of writership analysis | list | | |
example_cluster_template | handwriter | Example cluster template | list | | |
example_model | handwriter | Example of a hierarchical model | list | | |
london | handwriter | Cursive written word: London | matrix | 148 | |
message | handwriter | Full page image of the handwritten London letter. | matrix | 1262 | |
nature1 | handwriter | Full page image of the 4th sample (nature) of handwriting from the first writer. | matrix | 811 | |
twoSent | handwriter | Two sentence printed example handwriting | matrix | 396 | |
ipi_c_eu | RJDemetra | Industrial Production Indices in manufacturing industry in the European Union | mts | 372 | 34 |
KarnatakaForest | BIOMASS | Karnataka forest dataset | data.frame | 65889 | 8 |
NouraguesHD | BIOMASS | Height-Diameter data | data.frame | 1051 | 7 |
apgFamilies | BIOMASS | Angiosperm Phylogeny Group (APG III) dataset | data.frame | 502 | 2 |
feldCoef | BIOMASS | Feldpausch et al. 2012 coefficients for generalized height-diameter models | data.frame | 12 | 4 |
genusFamily | BIOMASS | Genus Family database | data.frame | 31355 | 2 |
param_4 | BIOMASS | Posterior distribution of Chave et al.'s 2014 equation 4 parameters | data.frame | 1001 | 3 |
param_7 | BIOMASS | Posterior distribution of parameters associated with the equation 7 by Chave et al. 2014. | data.frame | 1001 | 9 |
sd_10 | BIOMASS | Mean standard deviation of wood density estimates at different taxonomic levels | data.frame | 3 | 2 |
wdData | BIOMASS | The global wood density database | data.frame | 16467 | 7 |
LO_nb | spData | Lucas county OH housing | nb | | |
SplashDams | spData | Data for Splash Dams in western Oregon | SpatialPointsDataFrame | | |
afcon | spData | Spatial patterns of conflict in Africa 1966-78 | data.frame | 42 | 5 |
africa.rook.nb | spData | Spatial patterns of conflict in Africa 1966-78 | nb | | |
afxy | spData | Spatial patterns of conflict in Africa 1966-78 | matrix | 42 | |
aggregating_zones | spData | Datasets to illustrate the concept of spatial congruence | sf | 2 | 4 |
alaska | spData | Alaska multipolygon | sf | 1 | 7 |
auckland | spData | Marshall's infant mortality in Auckland dataset | data.frame | 167 | 4 |
auckland.nb | spData | Marshall's infant mortality in Auckland dataset | nb | | |
auckpolys | spData | Marshall's infant mortality in Auckland dataset | polylist | | |
baltimore | spData | House sales prices, Baltimore, MD 1978 | data.frame | 211 | 17 |
bbs | spData | Columbus OH spatial analysis data set | matrix | 49 | |
boston.c | spData | Corrected Boston Housing Data | data.frame | 506 | 20 |
boston.soi | spData | Corrected Boston Housing Data | nb | | |
boston.utm | spData | Corrected Boston Housing Data | matrix | 506 | 2 |
coffee_data | spData | World coffee production data | tbl_df | 47 | 3 |
col.gal.nb | spData | Columbus OH spatial analysis data set | nb | | |
columbus | spData | Columbus OH spatial analysis data set | data.frame | 49 | 22 |
congruent | spData | Datasets to illustrate the concept of spatial congruence | sf | 9 | 3 |
coords | spData | Columbus OH spatial analysis data set | matrix | 49 | |
cycle_hire | spData | Cycle hire points in London | sf | 742 | 6 |
cycle_hire_osm | spData | Cycle hire points in London from OSM | sf | 540 | 6 |
depmunic | spData | Municipality departments of Athens (Sf) | sf | 7 | 8 |
dll | spData | 1980 Presidential election results | nb | | |
e80_queen | spData | 1980 Presidential election results | nb | | |
eire.coords.utm | spData | Eire data sets | data.frame | 26 | 2 |
eire.df | spData | Eire data sets | data.frame | 26 | 9 |
eire.nb | spData | Eire data sets | nb | | |
eire.polys.utm | spData | Eire data sets | polylist | | |
elect80 | spData | 1980 Presidential election results | SpatialPointsDataFrame | | |
elect80_lw | spData | 1980 Presidential election results | listw | | |
go_x | spData | Getis-Ord remote sensing example data | numeric | | |
go_xyz | spData | Getis-Ord remote sensing example data | data.frame | 256 | 3 |
go_y | spData | Getis-Ord remote sensing example data | numeric | | |
hawaii | spData | Hawaii multipolygon | sf | 1 | 7 |
hopkins | spData | Hopkins burnt savanna herb remains | matrix | 40 | 40 |
house | spData | Lucas county OH housing | SpatialPointsDataFrame | | |
huddersfield | spData | Prevalence of respiratory symptoms | data.frame | 71 | 2 |
incongruent | spData | Datasets to illustrate the concept of spatial congruence | sf | 9 | 3 |
jenks71 | spData | Illinois 1959 county gross farm product value per acre | data.frame | 102 | 2 |
k4 | spData | 1980 Presidential election results | nb | | |
listw_NY | spData | New York leukemia data | listw | | |
lnd | spData | The boroughs of London | sf | 33 | 8 |
nc.sids | spData | North Carolina SIDS data | data.frame | 100 | 15 |
ncCC89.nb | spData | North Carolina SIDS data | nb | | |
ncCR85.nb | spData | North Carolina SIDS data | nb | | |
nydata | spData | New York leukemia data | data.frame | 281 | 12 |
nz | spData | Regions in New Zealand | sf | 16 | 7 |
nz_height | spData | High points in New Zealand | sf | 101 | 3 |
paper.nb | spData | Spatial patterns of conflict in Africa 1966-78 | nb | | |
polys | spData | Columbus OH spatial analysis data set | polylist | | |
properties | spData | Dataset of properties in the municipality of Athens (sf) | sf | 1000 | 7 |
seine | spData | Small river network in France | sf | 3 | 2 |
sidscents | spData | North Carolina SIDS data | matrix | 100 | |
sidspolys | spData | North Carolina SIDS data | polylist | | |
state.vbm | spData | US State Visibility Based Map | SpatialPolygonsDataFrame | | |
trMat | spData | Lucas county OH housing | numeric | | |
urban_agglomerations | spData | Major urban areas worldwide | sf | 540 | 10 |
us_states | spData | US states polygons | sf | 49 | 7 |
us_states_df | spData | the American Community Survey (ACS) data | tbl_df | 51 | 5 |
usa48.nb | spData | US 1960 used car prices | nb | | |
used.cars | spData | US 1960 used car prices | data.frame | 48 | 2 |
wheat | spData | Mercer and Hall wheat yield data | data.frame | 500 | 3 |
world | spData | World country polygons | sf | 177 | 11 |
worldbank_df | spData | World Bank data | tbl_df | 177 | 7 |
ba1986 | SimplyAgree | reps | data.frame | 17 | 5 |
recpre_long | SimplyAgree | Data | tbl_df | 30 | 6 |
reps | SimplyAgree | reps | data.frame | 20 | 3 |
temps | SimplyAgree | Data | tbl_df | 60 | 10 |
dps567 | FLa4a | | FLStock | | |
dps567.idx | FLa4a | | FLIndex | | |
hakeGSA7 | FLa4a | hakeGSA7 | FLStock | | |
hakeGSA7.idx | FLa4a | hakeGSA7.idx | FLIndices | | |
index_cd_len | FLa4a | index_cd_len | FLIndex | | |
index_pt_len | FLa4a | index_pt_len | FLIndex | | |
index_sp_len | FLa4a | index_sp_len | FLIndex | | |
mut09 | FLa4a | | FLStock | | |
mut09.idx | FLa4a | | FLIndices | | |
rfLen.stk | FLa4a | rfLen.stk | FLStockLen | | |
rfTrawl.idx | FLa4a | rfTrawl.idx | FLIndex | | |
rfTrawlJmp.idx | FLa4a | rfTrawlJmp.idx | FLIndex | | |
rfTrawlTrd.idx | FLa4a | rfTrawlTrd.idx | FLIndex | | |
shake_len | FLa4a | shake_len | FLStockLen | | |
codigos_ccaa | infoelectoral | Administrative codes for spanish autonomous communities. | tbl_df | 19 | 3 |
codigos_municipios | infoelectoral | Administrative codes for spanish municipalities. | tbl_df | 8135 | 3 |
codigos_partidos | infoelectoral | Recoded party names | tbl_df | 1057 | 4 |
codigos_provincias | infoelectoral | Administrative codes for spanish provinces. | tbl_df | 52 | 5 |
fechas_elecciones | infoelectoral | Election dates | tbl_df | 37 | 4 |
renta | infoelectoral | Mean income at the census section level (INE) | spec_tbl_df | 34680 | 2 |
bristol_od | spDataLarge | Datasets providing a snapshot of Bristol's transport system | tbl_df | 2910 | 7 |
bristol_region | spDataLarge | Datasets providing a snapshot of Bristol's transport system | sf | 1 | 2 |
bristol_stations | spDataLarge | Datasets providing a snapshot of Bristol's transport system | sf | 43 | 2 |
bristol_ttwa | spDataLarge | Datasets providing a snapshot of Bristol's transport system | sf | 1 | 2 |
bristol_ways | spDataLarge | Datasets providing a snapshot of Bristol's transport system | sf | 6160 | 4 |
bristol_zones | spDataLarge | Datasets providing a snapshot of Bristol's transport system | sf | 102 | 3 |
census_de | spDataLarge | Datasets providing building blocks for a location analysis | tbl_df | 361478 | 13 |
comm | spDataLarge | Community matrix of the Mt. Mongón | data.frame | 100 | 69 |
london_streets | spDataLarge | Streets of london downloaded from OSM | sf | 20972 | 2 |
lsl | spDataLarge | Landslide dataset from Southern Ecuador | data.frame | 350 | 8 |
metro_names | spDataLarge | Datasets providing building blocks for a location analysis | data.frame | 8 | 3 |
pol_pres15 | spDataLarge | Polish election data 2015 | sf | 2495 | 65 |
random_points | spDataLarge | Random points. | sf | 100 | 3 |
shops | spDataLarge | Datasets providing building blocks for a location analysis | sf | 104536 | 3 |
study_area | spDataLarge | Mask of the study area on the Mount Mongón | sf | 1 | 2 |
study_mask | spDataLarge | Landslide dataset from Southern Ecuador | sf | 1 | 2 |
zion_points | spDataLarge | Point vector data | sf | 30 | 1 |
fish | parameters | Sample data set | data.frame | 250 | 9 |
qol_cancer | parameters | Sample data set | data.frame | 564 | 7 |
Irish | seriation | Irish Referendum Data Set | matrix | 41 | 9 |
Munsingen | seriation | Hodson's Munsingen Data Set | matrix | 59 | 70 |
Psych24 | seriation | Results of 24 Psychological Test for 8th Grade Students | matrix | 24 | 24 |
SupremeCourt | seriation | Voting Patterns in the Second Rehnquist U.S. Supreme Court | matrix | 9 | 9 |
Townships | seriation | Bertin's Characteristics of Townships | matrix | 16 | 9 |
Wood | seriation | Gene Expression Data for Wood Formation in Poplar Trees | matrix | 136 | 6 |
Zoo | seriation | Zoo Data Set | data.frame | 101 | 17 |
chameleon_ds4 | seriation | 2D Data Sets used for the CHAMELEON Clustering Algorithm | data.frame | 8000 | 2 |
chameleon_ds5 | seriation | 2D Data Sets used for the CHAMELEON Clustering Algorithm | data.frame | 8000 | 2 |
chameleon_ds7 | seriation | 2D Data Sets used for the CHAMELEON Clustering Algorithm | data.frame | 10000 | 2 |
chameleon_ds8 | seriation | 2D Data Sets used for the CHAMELEON Clustering Algorithm | data.frame | 8000 | 2 |
example_sce | muscat | Example datasets | SingleCellExperiment | | |
sample.data.environment | LightLogR | Sample of wearable data combined with environmental data | grouped_df | 69120 | 3 |
mc_data_example_agg | myClim | Example data in Agg-format. | myClimList | | |
mc_data_example_clean | myClim | Example cleaned data in Raw-format. | myClimList | | |
mc_data_example_raw | myClim | Example data in Raw-format | myClimList | | |
mc_data_formats | myClim | Formats of source data files | environment | | |
mc_data_heights | myClim | Default heights of sensors | data.frame | 15 | 4 |
mc_data_physical | myClim | Physical quantities definition | environment | | |
mc_data_sensors | myClim | Sensors definition. | environment | | |
mc_data_vwc_parameters | myClim | Volumetric water content parameters | data.frame | 13 | 9 |
G0 | cda | Precomputed array factor for a square lattice at normal incidence | data.frame | 1000 | 3 |
gfun | cda | Precomputed array factor for a square lattice at normal incidence | list | | |
galaxy | bmixture | Galaxy data | matrix | 82 | 1 |
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 | | |
BCI | vegan | Barro Colorado Island Tree Counts | data.frame | 50 | 225 |
BCI.env | vegan | Barro Colorado Island Tree Counts | data.frame | 50 | 9 |
dune | vegan | Vegetation and Environment in Dutch Dune Meadows. | data.frame | 20 | 30 |
dune.env | vegan | Vegetation and Environment in Dutch Dune Meadows. | data.frame | 20 | 5 |
dune.phylodis | vegan | Taxonomic Classification and Phylogeny of Dune Meadow Species | dist | | |
dune.taxon | vegan | Taxonomic Classification and Phylogeny of Dune Meadow Species | data.frame | 30 | 5 |
mite | vegan | Oribatid Mite Data with Explanatory Variables | data.frame | 70 | 35 |
mite.env | vegan | Oribatid Mite Data with Explanatory Variables | data.frame | 70 | 5 |
mite.pcnm | vegan | Oribatid Mite Data with Explanatory Variables | data.frame | 70 | 22 |
mite.xy | vegan | Oribatid Mite Data with Explanatory Variables | data.frame | 70 | 2 |
pyrifos | vegan | Response of Aquatic Invertebrates to Insecticide Treatment | data.frame | 132 | 178 |
sipoo | vegan | Birds in the Archipelago of Sipoo (Sibbo and Borgå) | data.frame | 18 | 50 |
sipoo.map | vegan | Birds in the Archipelago of Sipoo (Sibbo and Borgå) | data.frame | 18 | 3 |
varechem | vegan | Vegetation and environment in lichen pastures | data.frame | 24 | 14 |
varespec | vegan | Vegetation and environment in lichen pastures | data.frame | 24 | 44 |
pisa | eatGADS | PISA Plus Example Data | GADSdat | | |
A | evola | Genotypic and Phenotypic data for a CP population | matrix | 363 | 363 |
A_wheat | evola | wheat lines dataset | matrix | 599 | 599 |
DT_cpdata | evola | Genotypic and Phenotypic data for a CP population | data.frame | 363 | 11 |
DT_technow | evola | Genotypic and Phenotypic data from single cross hybrids (Technow et al.,2014) | data.frame | 1254 | 6 |
DT_wheat | evola | wheat lines dataset | matrix | 599 | 4 |
GT_wheat | evola | wheat lines dataset | matrix | 599 | 1279 |
M_technow | evola | Genotypic and Phenotypic data from single cross hybrids (Technow et al.,2014) | matrix | 1254 | 1000 |
commune_names | rgugik | Communes in Poland | data.frame | 2477 | 2 |
county_names | rgugik | Counties in Poland | data.frame | 380 | 3 |
voivodeship_names | rgugik | Voivodeships in Poland | data.frame | 16 | 3 |
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 |
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 | | |
Jamaicatemp | GeoModels | December monthly average temperature in Jamaica between 1970-2000 | data.frame | 13530 | 3 |
anomalies | GeoModels | Annual precipitation anomalies in U.S. | matrix | 7352 | 3 |
austemp | GeoModels | Maximum australian temperature | matrix | 446 | 4 |
madagascarph | GeoModels | Soil ph of Madagascar | data.frame | 300649 | 3 |
spanish_wind | GeoModels | August monthly average wind speed in Spain between 1970-2000 | data.frame | 6000 | 3 |
winds | GeoModels | Irish Daily Wind Speeds | matrix | 6574 | 11 |
winds.coords | GeoModels | Weather Stations of the Irish Daily Wind Speeds | data.frame | 12 | 5 |
NS_interaction | mizer | Example interaction matrix for the North Sea example | matrix | 12 | 12 |
NS_params | mizer | Example MizerParams object for the North Sea example | MizerParams | | |
NS_sim | mizer | Example MizerSim object for the North Sea example | MizerSim | | |
NS_species_params | mizer | Example species parameter set based on the North Sea | data.frame | 12 | 8 |
NS_species_params_gears | mizer | Example species parameter set based on the North Sea with different gears | data.frame | 12 | 9 |
inter | mizer | Alias for 'NS_interaction' | matrix | 12 | 12 |
quitte_example_data | quitte | quitte example data | quitte | 19152 | 7 |
quitte_example_dataAR6 | quitte | quitte example data with three models (REMIND, GCAM, MESSAGEix) and two scenarios (Current Policies, Delayed transition) | quitte | 5040 | 7 |
remind_timesteps | quitte | REMIND time steps | tbl_df | 172 | 3 |
BankingCrisesDistances | cops | Banking Crises Distances | matrix | 69 | 70 |
matchphi | cops | Distances of MATCH-ADTC modules | distance | 32 | 32 |
MetRef | KODAMA | Nuclear Magnetic Resonance Spectra of Urine Samples | list | | |
USA | KODAMA | State of the Union Data Set | list | | |
clinical | KODAMA | Clinical Data of a Cohort of Prostate Cancer Patiens | data.frame | 105 | 5 |
lymphoma | KODAMA | Lymphoma Gene Expression Dataset | list | | |
contactmatrix_POLYMOD | hhh4contacts | POLYMOD Contact Matrices for Germany | matrix | 15 | 15 |
contactmatrix_POLYMOD_physical | hhh4contacts | POLYMOD Contact Matrices for Germany | matrix | 15 | 15 |
contactmatrix_mossong | hhh4contacts | POLYMOD Contact Matrices for Germany | matrix | 15 | 15 |
contactmatrix_mossong_physical | hhh4contacts | POLYMOD Contact Matrices for Germany | matrix | 15 | 15 |
contactmatrix_wallinga | hhh4contacts | POLYMOD Contact Matrices for Germany | matrix | 15 | 15 |
contactmatrix_wallinga_physical | hhh4contacts | POLYMOD Contact Matrices for Germany | matrix | 15 | 15 |
counts | hhh4contacts | Create '"sts"' Objects from the Berlin Norovirus Data | array | | |
map | hhh4contacts | Create '"sts"' Objects from the Berlin Norovirus Data | SpatialPolygonsDataFrame | | |
pop2011 | hhh4contacts | Berlin and German Population by Age Group, 2011 | matrix | 12 | 15 |
popDE | hhh4contacts | Berlin and German Population by Age Group, 2011 | integer | | |
ExampleData | ClusterVAR | Datasets included in the ClusterVAR package | matrix | 18000 | 8 |
SyntheticData | ClusterVAR | Datasets included in the ClusterVAR package | data.frame | 12998 | 10 |
ACValues | tseriesTARMA | Andrews Tabulated Critical Values | matrix | 13 | 62 |
supLMQur | tseriesTARMA | Tabulated Critical Values for the Unit Root IMA vs TARMA test | array | | |
CLASS | spheredata | Colorado Learning Attitudes about Science Survey (CLASS) dataset | tbl_df | 497 | 36 |
FCI | spheredata | Force Concept Inventory (FCI) dataset | tbl_df | 497 | 30 |
FCIkey | spheredata | Force Concept Inventory (FCI) key dataset | tbl_df | 1 | 30 |
FMCE | spheredata | Force and Motion Conceptual Evaluation (FMCE) dataset | tbl_df | 497 | 47 |
FMCEkey | spheredata | Force and Motion Conceptual Evaluation (FMCE) key dataset | tbl_df | 1 | 47 |
FMCI | spheredata | Fluid Mechanics Concept Inventory (FMCI) dataset | tbl_df | 497 | 30 |
FMCIkey | spheredata | Fluid Mechanics Concept Inventory (FMCI) key dataset | tbl_df | 1 | 30 |
MWCS | spheredata | Mechanical Waves Conceptual Survey (MWCS) dataset | tbl_df | 497 | 22 |
MWCSkey | spheredata | Mechanical Waves Conceptual Survey (MWCS) key dataset | tbl_df | 1 | 22 |
RRMCS | spheredata | Rotational and Rolling Motion Conceptual Survey (RRMCS) dataset | tbl_df | 497 | 30 |
RRMCSkey | spheredata | Rotational and Rolling Motion Conceptual Survey (RRMCS) key dataset | tbl_df | 1 | 30 |
SAAR | spheredata | Scientific Abilities Assessment Rubrics (SAAR) dataset | tbl_df | 497 | 16 |
STPFASL | spheredata | Survey of Thermodynamic Processes and First and Second Laws (STPFASL) dataset | tbl_df | 497 | 33 |
STPFASLkey | spheredata | Survey of Thermodynamic Processes and First and Second Laws (STPFASL) key dataset | tbl_df | 1 | 33 |
TCE | spheredata | Thermal Concept Evaluation (TCE) dataset | tbl_df | 497 | 26 |
TCEkey | spheredata | Thermal Concept Evaluation (TCE) key dataset | tbl_df | 1 | 26 |
demographic | spheredata | Students' demographic dataset | tbl_df | 497 | 13 |
literacy | spheredata | Students' literacy dataset | tbl_df | 497 | 2 |
physicsidentity | spheredata | Students' physics identity dataset | tbl_df | 497 | 2 |
teachersjudgment | spheredata | Teachers' judgment dataset | tbl_df | 497 | 3 |
closure_data | daedalus | Pandemic response strategy data for DAEDALUS | list | | |
country_codes_iso2c | daedalus | Country names and ISO codes for DAEDALUS | character | | |
country_codes_iso3c | daedalus | Country names and ISO codes for DAEDALUS | character | | |
country_data | daedalus | Country demographic data for DAEDALUS | list | | |
country_names | daedalus | Country names and ISO codes 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 | | |
life_value | daedalus | Values of statistical lives lost | list | | |
vaccination_parameter_names | daedalus | Vaccine investment scenario parameters | character | | |
vaccination_scenario_data | daedalus | Vaccine investment scenario parameters | list | | |
vaccination_scenario_names | daedalus | Vaccine investment scenario parameters | character | | |
hurricanes | DHARMa | Hurricanes | tbl_df | 92 | 14 |
mice.A | BGLR | Pedigree info for the mice dataset | matrix | 1814 | 1814 |
mice.X | BGLR | Molecular markers | matrix | 1814 | 10346 |
mice.map | BGLR | Genetic map info for the mice dataset | data.frame | 10346 | 4 |
mice.pheno | BGLR | Phenotypical data for the mice dataset | data.frame | 1814 | 38 |
simulated3t.X | BGLR | Molecular markers | matrix | 8000 | |
simulated3t.pheno | BGLR | Phenotypical data for simulated dataset with 3 traits | matrix | 8000 | 6 |
wheat.A | BGLR | Pedigree info for the wheat dataset | matrix | 599 | 599 |
wheat.X | BGLR | Molecular markers | matrix | 599 | 1279 |
wheat.Y | BGLR | Grain yield | matrix | 599 | 4 |
wheat.sets | BGLR | Sets for cross validation (CV) | integer | | |
dropRdemo | dropR | Demo Dataset for Dropout in an Online Survey | data.frame | 246 | 54 |
GTS2012 | palaeoverse | Geological Timescale 2012 | data.frame | 186 | 10 |
GTS2020 | palaeoverse | Geological Timescale 2020 | data.frame | 189 | 10 |
interval_key | palaeoverse | Example dataset: Interval key for the look_up function | data.frame | 1323 | 3 |
reefs | palaeoverse | Example dataset: Phanerozoic reefs from the PaleoReefs Database | data.frame | 4363 | 14 |
tetrapods | palaeoverse | Example dataset: Early tetrapod data from the Paleobiology Database | data.frame | 5270 | 32 |
ASEM_COIN | COINr | ASEM COIN (COINr < v1.0) | COIN | | |
ASEM_iData | COINr | ASEM raw indicator data | data.frame | 51 | 60 |
ASEM_iData_p | COINr | ASEM raw panel data | data.frame | 255 | 60 |
ASEM_iMeta | COINr | ASEM indicator metadata | data.frame | 68 | 10 |
WorldDenoms | COINr | World denomination data | tbl_df | 249 | 7 |
openxlsxFontSizeLookupTable | openxlsx | Font Size Lookup tables | data.frame | 29 | 225 |
openxlsxFontSizeLookupTableBold | openxlsx | Font Size Lookup tables | data.frame | 29 | 225 |
ctcv4_dir | chevron | CTC version 4 Grade Direction Data | data.frame | 35 | 3 |
ctcv5_dir | chevron | CTC version 5 Grade Direction Data | data.frame | 35 | 3 |
mla_dir | chevron | MLA Grade Direction Data | data.frame | 76 | 2 |
syn_data | chevron | Example 'adam' Synthetic Data | list | | |
buffalo | ctmm | African buffalo GPS dataset from Kruger National Park, South Africa. | list | | |
coati | ctmm | Coatis on Barro Colorado Island, Panama. | list | | |
gazelle | ctmm | Mongolian gazelle GPS dataset from the Mongolia's Eastern Steppe. | list | | |
jaguar | ctmm | Jaguar data from the Jaguar movement database. | list | | |
pelican | ctmm | Brown Pelican GPS and ARGOS data. | list | | |
turtle | ctmm | Wood turtle GPS and calibration dataset from Working Land and Seascapes. | list | | |
wolf | ctmm | Maned wolf GPS dataset from The Maned Wolf Conservation Program. | list | | |
Pentosan | PMCMRplus | Pentosan Dataset | data.frame | 189 | 3 |
algae | PMCMRplus | Algae Growth Inhibition Data Set | data.frame | 22 | 10 |
qPCR | PMCMRplus | qPCR Curve Analysis Methods | data.frame | 4 | 11 |
reviewers | PMCMRplus | Reviewers | matrix | 9 | 4 |
trout | PMCMRplus | Data from a Dose-Response Experiment with Trouts | data.frame | 65 | 5 |
globalTree | arakno | Global spider backbone tree. | phylo | | |
wscmap | arakno | Matrix matching WSC and ISO3 country codes. | data.frame | 799 | 257 |
binary | rsides | Example data set (binary endpoint) | data.frame | 359 | 11 |
continuous | rsides | Example data set (continuous endpoint) | data.frame | 359 | 11 |
survival | rsides | Example data set (time-to-event endpoint) | data.frame | 359 | 12 |
coleman | sna | Coleman's High School Friendship Data | array | | |
medical | packMBPLSDA | medical dataset | data.frame | 40 | 18 |
nutrition | packMBPLSDA | nutritional dataset | data.frame | 40 | 33 |
omics | packMBPLSDA | metabolomic dataset | data.frame | 40 | 46 |
status | packMBPLSDA | physiopathological status data | data.frame | 40 | 1 |
ar5_db_sample_data | mipplot | Sample Dataset | tbl_df | 25420 | 7 |
ar5_db_sample_rule_table | mipplot | Sample Rule Table | data.frame | 48 | 4 |
mipplot_default_color_palette | mipplot | Default color palette. | list | | |
sr15_sample_conversion_rule_table | mipplot | Sample Conversion Rule Table | data.frame | 37 | 6 |
sr15_sample_data | mipplot | Sample Dataset | tbl_df | 396425 | 7 |
AA_atlas | SSHAARP | Exon boundaries for all exons in protein coding genes in the IPD-IMGT/HLA Database release v 3.39.0 | list | | |
IMGTprotalignments | SSHAARP | Protein alignments for all protein coding genes in the IPD-IMGT/HLA Database release v 3.39.0. | list | | |
solberg_dataset | SSHAARP | Solberg Dataset | data.frame | 20163 | 13 |
HTP | ICSOutlier | Production Measurements of High-Tech Parts - Full Rank Case | data.frame | 902 | 88 |
HTP2 | ICSOutlier | Production Measurements of High-Tech Parts - Singular Case | data.frame | 457 | 149 |
HTP3 | ICSOutlier | Production Measurements of High-Tech Parts - Nearly Singular Case | data.frame | 371 | 33 |
adult | rebmix | Adult Dataset | data.frame | 48842 | 16 |
bearings | rebmix | Bearings Faults Detection Data | data.frame | 1906 | 14 |
galaxy | rebmix | Galaxy Dataset | data.frame | 82 | 1 |
iris | rebmix | Iris Data Set | data.frame | 150 | 5 |
sensorlessdrive | rebmix | Sensorless Drive Faults Detection Data | data.frame | 58509 | 4 |
steelplates | rebmix | Steel Plates Faults Recognition Data | data.frame | 1941 | 28 |
truck | rebmix | Truck Dataset | data.frame | 31665 | 2 |
weibull | rebmix | Weibull Dataset 8.1 | data.frame | 50 | 1 |
weibullnormal | rebmix | Weibull-normal Simulated Dataset | data.frame | 10000 | 2 |
wine | rebmix | Wine Recognition Data | data.frame | 178 | 14 |
GeneToEntrez | pubmed.mineR | Data containing Entrez Ids | data.frame | 21116 | 2 |
HGNC2UniprotID | pubmed.mineR | R Data containing HGNC2UniprotID data mapping. | data.frame | 67042 | 2 |
HGNCdata | pubmed.mineR | R Data containing HGNC data. | data.table | 42368 | 3 |
common_words_new | pubmed.mineR | R Data containing words which frequently in text | character | | |
NGSAustralia | gmGeostats | National Geochemical Survey of Australia: soil data | tbl_df | 5259 | 76 |
Windarling | gmGeostats | Ore composition of a bench at a mine in Windarling, West Australia. | data.frame | 1600 | 16 |
gsi.validModels | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.Exp | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.Exponential | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.Gau | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.Gauss | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.Sph | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.Spherical | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.exp | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.gauss | gmGeostats | Generate D-variate variogram models | numeric | | |
vg.sph | gmGeostats | Generate D-variate variogram models | numeric | | |
x12 | ppclust | Synthetic data set of two variables | matrix | 12 | 2 |
x16 | ppclust | Synthetic data set of two variables forming two clusters | data.frame | 16 | 3 |
car.insurance | unifed | Car insurance claims | data.frame | 67856 | 10 |
bathtub | textreg | Sample of cleaned OSHA accident summaries. | VCorpus | | |
dirtyBathtub | textreg | Sample of raw-text OSHA accident summaries. | data.frame | 127 | 335 |
testCorpora | textreg | Some small, fake test corpora. | list | | |
rcmb.rate | TriadSim | An example recombination rate dataset | data.frame | 412 | 4 |
snp.all2 | TriadSim | SNPs in the PLINK files | data.frame | 412 | 8 |
adult | fairml | Census Income | data.frame | 30162 | 14 |
bank | fairml | Bank Marketing | data.frame | 40195 | 19 |
communities.and.crime | fairml | Communities and Crime Data Set | data.frame | 1969 | 104 |
compas | fairml | Criminal Offenders Screened in Florida | data.frame | 5855 | 16 |
drug.consumption | fairml | Drug Consumption | data.frame | 1885 | 31 |
german.credit | fairml | German Credit Data | data.frame | 1000 | 21 |
health.retirement | fairml | Health and Retirement Survey | data.frame | 38653 | 27 |
law.school.admissions | fairml | Law School Admission Council data | data.frame | 20800 | 11 |
national.longitudinal.survey | fairml | Income and Labour Market Activities | data.frame | 4908 | 18 |
obesity.levels | fairml | Obesity Levels | data.frame | 2111 | 17 |
vu.test | fairml | Synthetic data set to test fair models | list | | |
sample | VectorCodeR | sample dataset | tbl_df | 101 | 3 |
rssimulxDemo.model | RsSimulx | Simulx project | character | | |
rssimulxDemo.project | RsSimulx | Simulx project | character | | |
ColoCan | gss | Colorectal Cancer Mortality Rate in Indiana Counties | data.frame | 184 | 11 |
DiaRet | gss | Diabetic Retinopathy | data.frame | 197 | 13 |
LakeAcidity | gss | Water Acidity in Lakes | data.frame | 112 | 5 |
NO2 | gss | Air Pollution and Road Traffic | data.frame | 500 | 6 |
Sachs | gss | Protein Expression in Human Immune System Cells | data.frame | 7466 | 12 |
aids | gss | AIDS Incubation | data.frame | 295 | 3 |
bacteriuria | gss | Treatment of Bacteriuria | data.frame | 820 | 4 |
buffalo | gss | Buffalo Annual Snowfall | numeric | | |
clim | gss | Average Temperatures During December 1980 Through February 1981 | data.frame | 690 | 2 |
esc | gss | Embryonic Stem Cell from Mouse | data.frame | 1027 | 8 |
eyetrack | gss | Eyesight Fixation in Eyetracking Experiments | data.frame | 13891 | 5 |
gastric | gss | Gastric Cancer Data | data.frame | 90 | 3 |
nox | gss | NOx in Engine Exhaust | data.frame | 88 | 3 |
ozone | gss | Ozone Concentration in Los Angeles Basin | data.frame | 330 | 10 |
penny | gss | Thickness of US Lincoln Pennies | data.frame | 90 | 2 |
stan | gss | Stanford Heart Transplant Data | data.frame | 184 | 4 |
wesdr | gss | Progression of Diabetic Retinopathy | data.frame | 669 | 4 |
wesdr1 | gss | Stages of Diabetic Retinopathy | data.frame | 2049 | 7 |
cell_type_biase | SparseDC | Biase Data Cell Type | character | | |
condition_biase | SparseDC | Biase Data Conditions | character | | |
data_biase | SparseDC | Biase Data | matrix | 16514 | 49 |
expdata | c3net | Example data set | matrix | 400 | 800 |
truenet | c3net | Reference, e.g. true, network of the example data set | matrix | 400 | |
Cloud | OPC | Cloud | data.frame | 1024 | 10 |
HTRU | OPC | HTRU | data.frame | 10000 | 9 |
Wine | OPC | Wine | data.frame | 177 | 13 |
banknote | otrimle | Swiss Banknotes Data | data.frame | 200 | 7 |
pregnandiol | kml3d | ~ Pregnandiol measure (from QUIDEL database, René Écochard) ~ | data.frame | 80 | 61 |
hares | phuassess | Radio-tracking data of European Brown Hares | list | | |
dy2009 | Spillover | Diebold and Yilmaz (2009) dataset | data.frame | 829 | 20 |
dy2012 | Spillover | Diebold and Yilmaz (2012) dataset | data.frame | 2771 | 5 |
rol.returns | Spillover | Two-days Rolling Average Returns | zoo | 1632 | 6 |
rol.vol | Spillover | Two-days Rolling Average Intra-day Volatilities | zoo | 1633 | 6 |
stock.prices | Spillover | Daily Stock Prices | zoo | 3507 | 6 |
All_header | OmnibusFisher | This is the data for examples | data.frame | 184 | 1 |
G | OmnibusFisher | This is the data for examples | list | | |
M | OmnibusFisher | This is the data for examples | list | | |
R | OmnibusFisher | This is the data for examples | list | | |
pheno | OmnibusFisher | This is the data for examples | data.frame | 175 | 4 |
J1709 | SOPIE | PSR J1709-44290 Time of Arrivals | numeric | | |
crab | SOPIE | PSR J0534+2200 (Crab-Pulsar) Time of Arrivals | numeric | | |
simdata | SOPIE | Simulated Data from a Scaled Von Mises Distribution with Noise | numeric | | |
ItalianCities | mpt | City-Size Paired-Comparison Task | data.frame | 64 | 6 |
MDHennig2020 | mpt | Moral Dilemma Judgment | data.frame | 16 | 7 |
MDreplication | mpt | Moral Dilemma Judgment | data.frame | 751 | 5 |
PMSmithBayen | mpt | Prospective Memory and Task Importance | data.frame | 24 | 5 |
PMreplication | mpt | Prospective Memory and Task Importance | data.frame | 72 | 5 |
ROCBroeder2009 | mpt | Recognition Receiver Operating Characteristics | data.frame | 20 | 7 |
ROCreplication | mpt | Recognition Receiver Operating Characteristics | data.frame | 48 | 5 |
WSTKlauer2007 | mpt | Wason Selection Task (WST) and Helpful Hints | data.frame | 32 | 4 |
WSTreplication | mpt | Wason Selection Task (WST) and Helpful Hints | data.frame | 1118 | 8 |
WorldCities | mpt | City-Size Paired-Comparison Task | data.frame | 37 | 6 |
proact | mpt | Recall Frequencies for DaPolito's Experiment on Proactive Inhibition | data.frame | 24 | 5 |
retroact | mpt | Recall Frequencies in Retroactive Inhibition | data.frame | 30 | 4 |
valence | mpt | World Valence and Source Memory for Vertical Position | data.frame | 128 | 5 |
gsta_data | binomialtrend | CRUTEM World Mean Temperature Data Set from 1851 to 2022 | data.frame | 172 | 4 |
artificialJointLongData | longitudinalData | ~ Data: artificialJointLongData ~ | data.frame | 150 | 34 |
artificialLongData | longitudinalData | ~ Data: artificialLongData ~ | data.frame | 200 | 12 |
gpcr | bios2mds | Pre-analyzed G-Protein-Coupled Receptor (GPCR) data set | list | | |
sub.mat | bios2mds | Amino acid substitution matrices | list | | |
Byar | clustMD | Byar prostate cancer data set. | data.frame | 475 | 15 |
PD4107a | ClusteredMutations | Somatic mutations data set from a primary breast cancer genome. | data.frame | 9879 | 5 |
AhRs | partitionMetric | Sample data for partitionMetric | matrix | 7 | |
kcm | ljr | Kentucky yearly cancer mortality from 1999-2005. | data.frame | 7 | 3 |
echo | MNARclust | Echocardiogram data set | data.frame | 132 | 13 |
myclimatic_data | MetGen | climatic data | data.frame | 4320 | 6 |
mycovariates | MetGen | Covariates data | data.frame | 4320 | 18 |
Hou_sim | ClussCluster | A truncated subset of the scRNA-seq expression data set from Hou et.al (2016) | list | | |
sim_dat | ClussCluster | A simulated expression data set. | matrix | 200 | |
epipageShort | kml | ~ Data: epipageShort ~ | data.frame | 697 | 6 |
antibio | aod | Antibiotics against Shipping Fever in Calves | data.frame | 24 | 3 |
cohorts | aod | Age, Period and Cohort Effects for Vital Rates | data.frame | 49 | 4 |
dja | aod | Mortality of Djallonke Lambs in Senegal | data.frame | 75 | 6 |
lizards | aod | A Comparison of Site Preferences of Two Species of Lizard | data.frame | 24 | 6 |
mice | aod | Pregnant Female Mice Experiment | data.frame | 20 | 3 |
orob1 | aod | Germination Data | data.frame | 16 | 3 |
orob2 | aod | Germination Data | data.frame | 21 | 4 |
rabbits | aod | Rabbits Foetuses Survival Experiment | data.frame | 84 | 3 |
rats | aod | Rats Diet Experiment | data.frame | 32 | 3 |
salmonella | aod | Salmonella Reverse Mutagenicity Assay | data.frame | 18 | 2 |
BrCa_1_AR | BCRA | Breast cancer 1-Attributable Risk | data.frame | 2 | 6 |
BrCa_beta | BCRA | Breast cancer beta | data.frame | 6 | 6 |
BrCa_lambda1 | BCRA | Breast cancer composite incidences | data.frame | 14 | 12 |
BrCa_lambda2 | BCRA | Breast cancer competing mortality | data.frame | 14 | 12 |
exampledata | BCRA | Example data set | data.frame | 26 | 9 |
immdef | rpsftm | immdef | data.frame | 1000 | 9 |
Coal | rankFD | Coal Acidity | data.frame | 18 | 3 |
Muco | rankFD | Half-Time of Mucociliary Clearance | data.frame | 14 | 2 |
nms | rankFD | Irritation of Nasal Mucosa | data.frame | 150 | 3 |
ethylene | rmp | Developmental toxicity study of ethylene glycol in mice | data.frame | 1192 | 7 |
sda | gamlss.inf | Data for using for simulation | data.frame | 120 | 5 |
flo | glmc | Internal glmc Objects | matrix | 16 | 16 |
ar1 | gif | Synthetic multivariate Gaussian data | list | | |
exp1 | acss | Data from Experiment 1 in Gauvrit, Singmann, Soler-Toscano & Zenil | data.frame | 34 | 2 |
exp2 | acss | Data from Experiment 2 in Gauvrit, Singmann, Soler-Toscano & Zenil | data.frame | 200 | 2 |
matthews2013 | acss | Data from Experiment 1 in Matthews (2013) | data.frame | 216 | 3 |
doll | msme | Physician smoking and mortality count data | data.frame | 10 | 9 |
heart | msme | Heart surgery outcomes for Canadian patients | data.frame | 15 | 5 |
medpar | msme | US national Medicare inpatient hospital database for Arizona patients. | data.frame | 1495 | 10 |
rwm5yr | msme | German health registry for the years 1984-1988 | data.frame | 19609 | 17 |
titanic | msme | Titanic passenger survival data | data.frame | 1316 | 4 |
ufc | msme | Upper Flat Creek forest cruise tree data | data.frame | 637 | 5 |
Melano | tdROC | Example data: Malignant Melanoma Data | data.frame | 205 | 4 |
mayo | tdROC | Example data: Mayo Data | data.frame | 312 | 4 |
berkeley | bsitar | Berkeley Child Guidance Study Data | tbl_df | 2883 | 10 |
berkeley_exdata | bsitar | Berkeley Child Guidance Study Data for females | data.frame | 770 | 3 |
berkeley_exfit | bsitar | Model fit to the Berkeley Child Guidance Study Data for females | brmsfit | | |
CTTdata | CTT | Example Multiple-Choice Data | data.frame | 100 | 20 |
CTTkey | CTT | Example Multiple-Choice Key | character | | |
datalist_imprimerie | logib | Imprimerie datalist | data.frame | 318 | 23 |
chicago | simsl | Air pollution dataset | data.frame | 5114 | 7 |
warfarin | simsl | Warfarin dataset | list | | |
exprs | SeqMADE | Gene Expression Dataset | data.frame | 100 | 15 |
networkModule | SeqMADE | NetworkModule | data.frame | 5 | 2 |
example | IDF | Sampled data for duration-dependent GEV | data.frame | 330 | 4 |
knee | GMMBoost | Clinical pain study on knee data | data.frame | 381 | 7 |
soccer | GMMBoost | German Bundesliga data for the seasons 2008-2010 | data.frame | 54 | 16 |
dat1 | OCA | Public data risk no. 1 | data.frame | 1000 | 1 |
dat2 | OCA | Public data risk no. 2 | data.frame | 400 | 1 |
DadosFat | MultipleRegression | Dados de exemplo de um experimento sem repeticoes. | data.frame | 100 | 4 |
DadosPalma | MultipleRegression | Dados de exemplo de um experimento sem repeticoes. | data.frame | 100 | 7 |
X163204843_1 | TrafficBDE | Sample data from Traffic BDE | tbl_df | 226 | 11 |
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 |
df | trendchange | Example Data Frame for Innovative Polygon Trend Analysis | data.frame | 12 | 3 |
x | trendchange | Annual flow of the Nile River | numeric | | |
arsefigures | arse | arsefigures | data.frame | 10 | 22 |
stress_appraisal | arse | stress_appraisal | data.frame | 50 | 12 |
ForgedBankNotes | FRB | Swiss (forged) bank notes data | data.frame | 100 | 6 |
schooldata | FRB | School Data | data.frame | 70 | 8 |
NBSdiff1kg | longmemo | NBS measurement deviations from 1 kg | ts | | |
NhemiTemp | longmemo | Northern Hemisphere Temperature | ts | | |
NileMin | longmemo | Nile River Minima, yearly 622-1284 | ts | | |
ethernetTraffic | longmemo | Ethernet Traffic Data Set | ts | | |
videoVBR | longmemo | Video VBR data | ts | | |
DominoData | DominoEffect | Sample data | data.frame | 20300 | 5 |
SnpData | DominoEffect | Sample data | data.frame | 423 | 3 |
TestData | DominoEffect | Sample data | data.frame | 1820 | 8 |
clin.crc | CINdex | Colon cancer clinical dataset | matrix | 10 | 2 |
cnvgr.18.auto | CINdex | Probe annotation file for Affymetrix Genome Wide Human SNP Array 6.0 | GRanges | | |
cyto.cin4heatmap | CINdex | Cytoband CIN T-test output | matrix | 22 | 10 |
cytobands.cin | CINdex | Cytoband CIN dataset | list | | |
geneAnno | CINdex | CDS gene annotation file | matrix | 219264 | 5 |
grl.data | CINdex | Output of segmentation algorithm | CompressedGRangesList | | |
hg18.ucsctrack | CINdex | Human reference annotation file | GRanges | | |
snpgr.18.auto | CINdex | Probe annotation file for Affymetrix Genome Wide Human SNP Array 6.0 | GRanges | | |
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 | | |
X | jtdm | Site x environmental covariates dataset | matrix | 116 | 3 |
Y | jtdm | Site x CWM traits dataset | matrix | 116 | 3 |
g2g_data | vivainsights | Sample Group-to-Group dataset | spec_tbl_df | 150 | 11 |
mt_data | vivainsights | Sample Meeting Query dataset | spec_tbl_df | 612 | 41 |
p2p_data | vivainsights | Sample person-to-person dataset | tbl_df | 11550 | 13 |
pq_data | vivainsights | Sample Person Query dataset | spec_tbl_df | 1000 | 154 |
barley | paar | Barley grain yield | data.frame | 7394 | 3 |
wheat | paar | Database from a production field under continuous agriculture | data.frame | 5982 | 7 |
bf_data | florabr | Flora e Funga do Brasil database - Version 393.401 | data.frame | 50239 | 23 |
biomes | florabr | SpatVector of the biomes of Brazil | PackedSpatVector | | |
brazil | florabr | SpatVector of the Brazil's national borders | PackedSpatVector | | |
occurrences | florabr | Records of plant species | data.frame | 1658 | 3 |
states | florabr | SpatVector of the federal states of Brazil | PackedSpatVector | | |
gaa | k5 | GAA Team Abbreviations by Season and Team ID | tbl_df | 94 | 3 |
counts_example | BREADR | counts_example | tbl_df | 15 | 4 |
relatedness_example | BREADR | relatedness_example | tbl_df | 15 | 12 |
Movies | descriptio | Movies (data) | data.frame | 1000 | 7 |
parent_child_income | csranks | Income of parents and children | data.frame | 3894 | 4 |
pisa | csranks | Cross-country comparison of students' achievement | data.frame | 37 | 7 |
pisa2018 | csranks | Cross-country comparison of students' achievement | data.frame | 38 | 7 |
pisa2022 | csranks | Cross-country comparison of students' achievement | data.frame | 38 | 7 |
two_half_moons | CCMMR | Two interlocking half moons data set | data.frame | 150 | 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 |
IK | rioja | Imbrie and Kipp foraminifera data | list | | |
Ponds | rioja | Southeast England ponds and pools diatom and water chemistry dataset. | list | | |
RLGH | rioja | Diatom stratigraphic data from the Round Loch of Glenhead, Galloway, Southwest Scotland | list | | |
SWAP | rioja | SWAP surface sediment diatom data and lake-water pH. | list | | |
aber | rioja | Abernethy Forest pollen data | list | | |
Crowther2003 | metasens | Aspirin after Myocardial Infarction | data.frame | 9 | 5 |
Moore1998 | metasens | NSAIDS in acute pain | data.frame | 37 | 5 |
base_heterocp | unitdid | Simulated Individual Child Panalty Data | tbl_df | 260360 | 5 |
clusters.adt | scviR | ADT-based cluster labels for 7472 cells in OSCA chapter 12 analysis | factor | | |
clusters.rna | scviR | mRNA-based cluster labels for 7472 cells in OSCA chapter 12 analysis | factor | | |
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 |
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 |
dat | SSVS | Example dataset for 'ssvs' function @format A data frame with 74 records and 76 variables | data.frame | 74 | 76 |
chi_citations | crandep | Citation network of CHI papers | tbl_df | 31951 | 4 |
cran_dependencies | crandep | Dependencies of CRAN packages | spec_tbl_df | 211381 | 4 |
BUSseqfits_example | BUSseq | An external example of the output of the 'BUSseq_MCMC' | SingleCellExperiment | | |
DataApes | RRphylo | Example dataset | list | | |
DataCetaceans | RRphylo | Example dataset | list | | |
DataFelids | RRphylo | Example dataset | list | | |
DataOrnithodirans | RRphylo | Example dataset | list | | |
DataSimians | RRphylo | Example dataset | list | | |
DataUng | RRphylo | Example dataset | list | | |
HHSpain | repolr | Harris Hip Pain Scores | data.frame | 174 | 4 |
QoL | repolr | Quality of Life Scores | data.frame | 336 | 4 |
achilles | repolr | Achilles Tendon Rupture | data.frame | 144 | 4 |
begonia | repolr | Begonia Pot Plant Quality Scores | data.frame | 720 | 16 |
mobility | repolr | Mobility after Hip Fracture Fixation Surgery | data.frame | 600 | 6 |
ipddata | crossnma | Simulated individual participant dataset. | data.frame | 1944 | 10 |
stddata | crossnma | Simulated aggregate dataset. | data.frame | 4 | 11 |
gtrigsamples | lorad | Sequence data used in gtrig vignette | data.frame | 10001 | 35 |
k80samples | lorad | Sequence data used in k80 vignette | data.frame | 10000 | 4 |
linked_sim | multinets | A simulated multilevel network | igraph | | |
linked_sim_matrix | multinets | A simulated multilevel network | matrix | 150 | |
linked_sim_type | multinets | A simulated multilevel network | logical | | |
raw_tweets | saotd | Twitter Data Set | tbl_df | 14483 | 6 |
aemet_temp | goffda | AEMET daily temperatures during 1974-2013 | list | | |
ontario | goffda | Ontario temperature and electricity consumption during 2010-2014 | list | | |
sim102 | dcanr | Simulated expression data with knock-outs | list | | |
arab | NBPSeq | Arabidopsis RNA-Seq Data Set | matrix | 26222 | 6 |
hawkins | MonoPoly | hawkins | data.frame | 50 | 2 |
w0 | MonoPoly | Simulated w0 data used in Murray et al. (2013) | data.frame | 21 | 2 |
w2 | MonoPoly | Simulated w2 data used in Murray et al. (2013) | data.frame | 41 | 2 |
contax.trim | microcontax | The ConTax data set | data.frame | 38781 | 2 |
medoids | microcontax | The ConTax medoids | data.frame | 1774 | 2 |
taxonomy.table | microcontax | Taxonomy look-up table | data.frame | 2296 | 7 |
loc_data_2019 | stopdetection | Timestamped Location Data | data.table | 21911 | 3 |
fishing | camerondata | Fishing mode choice | tbl_df | 1182 | 16 |
incpanel | camerondata | Hourly wages | spec_tbl_df | 4856 | 9 |
jobless | camerondata | Unemployment duration | tbl_df | 3343 | 43 |
laborpanel | camerondata | Hours worked and wages | tbl_df | 5320 | 8 |
laborpanelprec | camerondata | Hours worked and wages (more precision) | tbl_df | 5320 | 8 |
nswproject | camerondata | Training and earnings | tbl_df | 2675 | 18 |
patentsrd | camerondata | Patents and R&D | tbl_df | 346 | 25 |
randhealth | camerondata | Health expenditures and insurance plans | tbl_df | 20190 | 45 |
schooling | camerondata | Returns to schooling | tbl_df | 5226 | 101 |
strikes | camerondata | Strikes duration | tbl_df | 566 | 2 |
vietnam_hh | camerondata | Vietnam health care use (household level) | tbl_df | 5999 | 8 |
vietnam_ind | camerondata | Vietnam health care use (individual level) | tbl_df | 27766 | 12 |
vietnamlss | camerondata | Household medical expenditure | tbl_df | 5999 | 9 |
CCLEsmall | PharmacoGx | Cancer Cell Line Encyclopedia (CCLE) Example PharmacoSet | PharmacoSet | | |
CMAPsmall | PharmacoGx | Connectivity Map Example PharmacoSet | PharmacoSet | | |
GDSCsmall | PharmacoGx | Genomics of Drug Sensitivity in Cancer Example PharmacoSet | PharmacoSet | | |
HDAC_genes | PharmacoGx | HDAC Gene Signature | data.frame | 14 | 2 |
abc | idem | Example dataset | data.frame | 187 | 5 |
arabidopsis_TEs | methimpute | Transposable element coordinates for Arabidopsis (chr1) | GRanges | | |
arabidopsis_chromosomes | methimpute | Chromosome lengths for Arabidopsis | data.frame | 7 | 2 |
arabidopsis_genes | methimpute | Gene coordinates for Arabidopsis (chr1) | GRanges | | |
arabidopsis_toydata | methimpute | Toy data for Arabidopsis (200.000bp of chr1) | GRanges | | |
body_fat | ODRF | Body Fat Prediction Dataset | data.frame | 252 | 15 |
breast_cancer | ODRF | Breast Cancer Dataset | data.frame | 569 | 32 |
seeds | ODRF | seeds Data Set | data.frame | 209 | 8 |
sample.matrix | UCell | Sample dataset to test UCell installation | dgCMatrix | | |
cesc | ordinalbayes | Data Frame of Smaller Subset of The Cancer Genome Atlas Cervical Cancer HTSeq Data. | data.frame | 242 | 45 |
finalSet | ordinalbayes | Subset of The Cancer Genome Atlas Cervical Cancer HTSeq Data. | DESeqTransform | | |
reducedSet | ordinalbayes | Smaller Subset of The Cancer Genome Atlas Cervical Cancer HTSeq Data. | DESeqTransform | | |
COPD_131 | MSPrep | Example mass spectrometry dataset | data.frame | 662 | 396 |
msquant | MSPrep | Example mass spectrometry dataset. | data.frame | 2644 | 56 |
GarwayHeath | spCP | Garway-Heath angles for the HFA-II | numeric | | |
HFAII_Queen | spCP | HFAII Queen Adjacency Matrix | matrix | 54 | |
HFAII_QueenHF | spCP | HFAII Queen Hemisphere Adjacency Matrix | matrix | 54 | |
HFAII_Rook | spCP | HFAII Rook Adjacency Matrix | matrix | 54 | |
VFSeries | spCP | Visual field series for one patient. | data.frame | 486 | 4 |
covComb_tx_deg | qsvaR | RSE object of RNA-seq data that serves as output for degradation analysis | RangedSummarizedExperiment | | |
degradation_tstats | qsvaR | Degradation time t-statistics | data.frame | 45082 | 1 |
transcripts | qsvaR | Transcripts for Degradation Models | list | | |
beaches | peptools | Bathing beaches | sf | 28 | 4 |
dodat | peptools | Dissolved oxygen data for USGS stations | data.frame | 1859479 | 3 |
entdat | peptools | Raw beach pathogen data from Suffolk County | data.frame | 4989 | 5 |
pepseg | peptools | Polygon shapefile of segment boundaries | sf | 61 | 2 |
pepstations | peptools | Bay stations by segment | tbl_df | 46 | 5 |
peptargets | peptools | Bay segment targets | tbl_df | 4 | 5 |
rawdat | peptools | Raw data from Suffolk County | tbl_df | 37539 | 11 |
Boston_df | usdatasets | Housing Values in Suburbs of Boston | data.frame | 506 | 14 |
Cars93_df | usdatasets | Data from 93 Cars on Sale in the USA in 1993 | tbl_df | 54 | 6 |
UCBAdmissions_table | usdatasets | Student Admissions at UC Berkeley | table | | |
USAccDeaths_ts | usdatasets | Accidental Deaths in the US 1973-1978 | ts | | |
USArrests_df | usdatasets | Violent Crime Rates by US State | data.frame | 50 | 4 |
USJudgeRatings_df | usdatasets | Lawyers' Ratings of State Judges in the US Superior Court | data.frame | 43 | 12 |
USPersonalExpenditure_matrix | usdatasets | Personal Expenditure Data | matrix | 5 | 5 |
UScitiesD_dist | usdatasets | Distances Between European Cities and Between US Cities | dist | | |
VADeaths_matrix | usdatasets | Death Rates in Virginia (1940) | matrix | 5 | 4 |
acs12_tbl_df | usdatasets | American Community Survey 2012 | tbl_df | 2000 | 13 |
age_at_mar_tbl_df | usdatasets | Age at first marriage of 5,534 US women. | tbl_df | 5534 | 1 |
airlines_tbl_df | usdatasets | Airline names - U.S. Airlines Carrier Codes and Names | tbl_df | 16 | 2 |
airports_tbl_df | usdatasets | Airport metadata - U.S. Airports Information | tbl_df | 1458 | 8 |
airquality_df | usdatasets | New York Air Quality Measurements | data.frame | 153 | 6 |
ames_tbl_df | usdatasets | Housing prices in Ames, Iowa | tbl_df | 2930 | 82 |
births14_tbl_df | usdatasets | US Births 2014 | tbl_df | 1000 | 13 |
births_tbl_df | usdatasets | North Carolina births, 100 cases | tbl_df | 150 | 9 |
census_tbl_df | usdatasets | Random sample of 2000 U.S. Census Data | tbl_df | 500 | 8 |
cia_factbook_tbl_df | usdatasets | CIA Factbook Details on Countries | tbl_df | 259 | 11 |
cle_sac_tbl_df | usdatasets | Cleveland and Sacramento Demographic and Income Data (2000) | tbl_df | 500 | 8 |
county_tbl_df | usdatasets | United States Counties | tbl_df | 3142 | 15 |
env_regulation_tbl_df | usdatasets | American Adults on Regulation and Renewable Energy | tbl_df | 705 | 1 |
fcid_tbl_df | usdatasets | Summary of male heights from USDA Food Commodity Intake Database | tbl_df | 100 | 2 |
goog_tbl_df | usdatasets | Google stock data | tbl_df | 98 | 7 |
govrace10_tbl_df | usdatasets | Election results for 2010 Governor races in the U.S. | tbl_df | 37 | 23 |
homicides15_tbl_df | usdatasets | Homicides in nine cities in 2015 | tbl_df | 1922 | 15 |
house_tbl_df | usdatasets | United States House of Representatives historical make-up | tbl_df | 116 | 12 |
houserace10_tbl_df | usdatasets | Election results for the 2010 U.S. House of Represenatives races | tbl_df | 435 | 24 |
immigration_tbl_df | usdatasets | Poll on illegal workers in the US | tbl_df | 910 | 2 |
leg_mari_tbl_df | usdatasets | Legalization of Marijuana Support in 2010 California Survey | tbl_df | 119 | 1 |
marathon_tbl_df | usdatasets | New York City Marathon Times (outdated) | tbl_df | 59 | 3 |
military_tbl_df | usdatasets | US Military Demographics | tbl_df | 1414593 | 6 |
minn38_df | usdatasets | Minnesota High School Graduates of 1938 | data.frame | 168 | 5 |
mlb_players_18_tbl_df | usdatasets | Batter Statistics for 2018 Major League Baseball (MLB) Season | tbl_df | 1270 | 19 |
mn_police_use_of_force_df | usdatasets | Minneapolis police use of force data. | data.frame | 12925 | 13 |
nba_players_19_tbl_df | usdatasets | NBA Players for the 2018-2019 season | tbl_df | 494 | 7 |
ncbirths_tbl_df | usdatasets | North Carolina births, 1000 cases | tbl_df | 1000 | 13 |
nyc_marathon_tbl_df | usdatasets | New York City Marathon Times | tbl_df | 102 | 7 |
nycvehiclethefts_tbl_df | usdatasets | Thefts of motor vehicles 2014 to 2017 | tbl_df | 35746 | 9 |
offshore_drilling_tbl_df | usdatasets | California poll on drilling off the California coast | tbl_df | 828 | 2 |
orings_tbl_df | usdatasets | 1986 Challenger disaster and O-rings | tbl_df | 23 | 4 |
oscars_tbl_df | usdatasets | Oscar winners, 1929 to 2018 | tbl_df | 184 | 11 |
piracy_tbl_df | usdatasets | Piracy and PIPA/SOPA | tbl_df | 534 | 8 |
precip_numeric | usdatasets | Annual Precipitation in US Cities | numeric | | |
presidents_ts | usdatasets | Quarterly Approval Ratings of US Presidents | ts | | |
prrace08_tbl_df | usdatasets | Election results for the 2008 U.S. Presidential race | tbl_df | 51 | 7 |
road_df | usdatasets | Road Accident Deaths in US States | data.frame | 26 | 6 |
senaterace10_tbl_df | usdatasets | Election results for the 2010 U.S. Senate races | tbl_df | 38 | 23 |
sp500_1950_2018_tbl_df | usdatasets | Daily observations for the S&P 500 - Historical Data (1950-2018) | tbl_df | 17346 | 7 |
sp500_tbl_df | usdatasets | Financial information for 50 S&P 500 companies | tbl_df | 50 | 12 |
state_abb_character | usdatasets | US State Facts and Figures - U.S. State Abbreviations | character | | |
state_area_numeric | usdatasets | US State Facts and Figures - US State Areas | numeric | | |
state_center_list | usdatasets | US State Facts and Figures - US State Centers | list | | |
state_division_factor | usdatasets | US State Facts and Figures - US State Divisions | factor | | |
state_name_character | usdatasets | US State Facts and Figures - US State Names | character | | |
state_region_factor | usdatasets | US State Facts and Figures - US State Regions | factor | | |
state_x77_matrix | usdatasets | US State Facts and Figures - US State Demographics and Statistics (1977) | matrix | 50 | 8 |
us_crime_rates_spec_tbl_df | usdatasets | US Crime Rates | spec_tbl_df | 60 | 12 |
us_temp_tbl_df | usdatasets | US Temperature Data | tbl_df | 10118 | 9 |
us_time_survey_tbl_df | usdatasets | American Time Survey 2009 - 2019 | tbl_df | 11 | 8 |
uspop_ts | usdatasets | Populations Recorded by the US Census | ts | | |
voter_count_spec_tbl_df | usdatasets | US Voter Turnout Data. | spec_tbl_df | 936 | 7 |
women_df | usdatasets | Average Heights and Weights for American Women | data.frame | 15 | 2 |
combinations.partial | ERSSA | Example list of combinations generated by comb_gen function. | list | | |
condition_table.full | ERSSA | Example table of sample names and conditions | data.frame | 20 | 2 |
condition_table.partial | ERSSA | Example table of sample names and conditions | data.frame | 8 | 2 |
count_table.filtered.partial | ERSSA | Example count table of GTEx RNA-seq experiment, fitered by count_filter function | data.frame | 974 | 8 |
count_table.full | ERSSA | Example count table of GTEx RNA-seq experiment | data.frame | 58037 | 20 |
count_table.partial | ERSSA | Example count table of GTEx RNA-seq experiment | data.frame | 1000 | 8 |
deg.partial | ERSSA | Example list of DE genes generated by edgeR | list | | |
NCI60 | missRows | Data of the NCI-60 Cell Lines with Missing Individuals | list | | |
testDF | ModelMetrics | Test data | data.frame | 100 | 3 |
theta0 | first90 | | numeric | | |
SPECS | seasonal | List of Available X-13ARIMA-SEATS Outputs | data.frame | 380 | 6 |
cny | seasonal | Dates of Chinese New Year, Indian Diwali and Easter | Date | | |
cpi | seasonal | Consumer Price Index of Switzerland | ts | | |
diwali | seasonal | Dates of Chinese New Year, Indian Diwali and Easter | Date | | |
easter | seasonal | Dates of Chinese New Year, Indian Diwali and Easter | Date | | |
exp | seasonal | Exports and Imports of China | ts | | |
iip | seasonal | Industrial Production of India | ts | | |
imp | seasonal | Exports and Imports of China | ts | | |
unemp | seasonal | United States Unemployment Level | ts | | |
mdb_tbl | selfdestructin5 | mdb_tbl: Example Data Set | tbl_df | 16 | 6 |
simData | dejaVu | Simulated recurrent event data. | data.frame | 500 | 3 |
majors | ggalluvial | Students' declared majors across several semesters | data.frame | 80 | 3 |
vaccinations | ggalluvial | Influenza vaccination survey responses | data.frame | 117 | 6 |
ail | VSURF | Real-world data on PM10 pollution in Rouen area, France | data.frame | 1096 | 15 |
gcm | VSURF | Real-world data on PM10 pollution in Rouen area, France | data.frame | 1096 | 16 |
gui | VSURF | Real-world data on PM10 pollution in Rouen area, France | data.frame | 1096 | 18 |
hri | VSURF | Real-world data on PM10 pollution in Rouen area, France | data.frame | 1096 | 18 |
jus | VSURF | Real-world data on PM10 pollution in Rouen area, France | data.frame | 1096 | 18 |
rep | VSURF | Real-world data on PM10 pollution in Rouen area, France | data.frame | 1096 | 18 |
toys | VSURF | A simulated dataset called toys data | list | | |
anxiety | ura | Anxiety ratings | tbl_df | 60 | 3 |
diagnoses | ura | Psychiatric diagnoses of patients | tbl_df | 180 | 3 |
daily_returns | HierPortfolios | Daily returns (in percentage) of 15 assets. | data.frame | 2559 | 15 |
mldp_returns | HierPortfolios | Returns of 10 simulated assets. | data.frame | 10000 | 10 |
gen_di_det_ex | ipmr | A general deterministic IPM example | general_di_det_ipm | | |
iceplant_ex | ipmr | Raw demographic data to construct an example IPM | data.frame | 288 | 10 |
monocarp_proto | ipmr | A 'proto_ipm' for a monocarpic perennial | simple_di_det | 2 | 15 |
sim_di_det_ex | ipmr | Simple deterministic IPM example | simple_di_det_ipm | | |
Athaliana_ODE | GRENITS | Gene expression time series generated with ODE model | data.frame | 5 | 50 |
Athaliana_ODE_4NoiseReps | GRENITS | Gene expression time series generated with ODE model with added noise | data.frame | 5 | 200 |
smokers | pairkat | Smokers - PaIRKAT Example Data | SummarizedExperiment | | |
germany_covid19_hosp | epinowcast | Hospitalisations in Germany by date of report and reference | data.table | 1536885 | 5 |
dataCSL | RISCA | CSL Liver Chirrosis Data. | data.frame | 2481 | 12 |
dataDIVAT1 | RISCA | A First Sample From The DIVAT Data Bank. | data.frame | 5943 | 7 |
dataDIVAT2 | RISCA | A Second Sample From the DIVAT Data Bank. | data.frame | 1837 | 6 |
dataDIVAT3 | RISCA | A Third Sample From the DIVAT Data Bank. | data.frame | 4267 | 8 |
dataDIVAT4 | RISCA | A Fourth Sample From the DIVAT Data Bank. | data.frame | 6648 | 3 |
dataDIVAT5 | RISCA | The Aggregated Kidney Graft Survival Stratified By The 1-year Serum Creatinine. | data.frame | 106 | 9 |
dataFTR | RISCA | Data for First Kidney Transplant Recipients. | data.frame | 2206 | 4 |
dataHepatology | RISCA | The Data Extracted From The Meta-Analysis By Cabibbo et al. (2010). | data.frame | 317 | 8 |
dataKTFS | RISCA | A Sixth Sample Of The DIVAT Cohort. | data.frame | 2169 | 3 |
dataKi67 | RISCA | The Aggregated Data Published By de Azambuja et al. (2007). | data.frame | 437 | 11 |
dataOFSEP | RISCA | A Simulated Sample From the OFSEP Cohort. | data.frame | 1300 | 11 |
dataSTR | RISCA | Data for Second Kidney Transplant Recipients. | data.frame | 546 | 6 |
fr.ratetable | RISCA | Expected Mortality Rates of the General French Population | ratetable | | |
geneInfo | CNTools | method that convert segment data into reduced segment matrix | data.frame | 28918 | 5 |
sampleData | CNTools | Class "CNSeg" contains the output of DNACopy segmentation data that can be operated on by the associated methods | data.frame | 54825 | 6 |
turtles | Morphoscape | Turtle Humeri | data.frame | 40 | 4 |
turtles_tree | Morphoscape | Trutle Phylogeny | phylo | | |
warps | Morphoscape | Simulated Shape Warps | data.frame | 24 | 6 |
bilby | PopGenReport | Bilby data set | genind | | |
landgen | PopGenReport | A simulated genind data set with spatial coordinates | genind | | |
possums | PopGenReport | A genlight object created via the read.genetable functions [possum data set from Sarre et al. 2015] | genind | | |
Ecoli.expr | sand | E. coli gene expression levels | matrix | 40 | 153 |
aidsblog | sand | AIDS blog citation network | igraph | | |
calldata | sand | Austrian phone call network data | data.frame | 992 | 7 |
delaydata | sand | Internet packet probes data | data.frame | 9567 | 3 |
elist.lazega | sand | Lazega lawyers network data | data.frame | 115 | 2 |
fblog | sand | Network of French political blogs | igraph | | |
g.bip | sand | A toy bipartite network | igraph | | |
hc | sand | Hospital encounter network data | data.frame | 32424 | 5 |
host.locs | sand | Internet packet probes data | character | | |
lazega | sand | Lazega lawyers network data | igraph | | |
ppi.CC | sand | Yeast protein interaction network | igraph | | |
regDB.adj | sand | E. coli gene expression levels | matrix | 153 | 153 |
strike | sand | Michael's strike network | igraph | | |
v.attr.lazega | sand | Lazega lawyers network data | data.frame | 36 | 9 |
area_unit_options | sfext | Area units (vector) | character | | |
dist_unit_options | sfext | Distance units (vector) | character | | |
dist_units | sfext | Distance units (data frame) | tbl_df | 33 | 12 |
paper_sizes | sfext | Standard paper and image sizes | tbl_df | 125 | 9 |
standard_scales | sfext | Standard map, architectural, and engineering scales | tbl_df | 36 | 16 |
citytemp | highcharter | City temperatures from a year in wide format | tbl_df | 12 | 5 |
citytemp_long | highcharter | City temperatures from a year in long format | tbl_df | 36 | 3 |
favorite_bars | highcharter | Marshall's Favorite Bars | tbl_df | 5 | 2 |
favorite_pies | highcharter | Marshall's Favorite Pies | tbl_df | 5 | 2 |
globaltemp | highcharter | globaltemp | tbl_df | 1992 | 4 |
mountains_panorama | highcharter | Visual comparison of Mountains Panorama | tbl_df | 91 | 3 |
pokemon | highcharter | pokemon | tbl_df | 898 | 24 |
stars | highcharter | stars | tbl_df | 404 | 6 |
unemployment | highcharter | US Counties unemployment rate | tbl_df | 3216 | 3 |
uscountygeojson | highcharter | US Counties map in Geojson format (list) | list | | |
usgeojson | highcharter | US States map in Geojson format (list) | list | | |
vaccines | highcharter | Vaccines | tbl_df | 3876 | 3 |
weather | highcharter | Weather | tbl_df | 365 | 4 |
worldgeojson | highcharter | World map in Geojson format (list) | list | | |
ecospat.testData | ecospat | Test Data For The Ecospat package | data.frame | 300 | 96 |
ecospat.testMdr | ecospat | Test Data For The ecospat.mdr function | data.frame | 102 | 3 |
ecospat.testNiche | ecospat | Test Data For The Niche Overlap Analysis | data.frame | 99 | 4 |
ecospat.testNiche.inv | ecospat | Test Data For The Niche Dynamics Analysis In The Invaded Range Of A Hypothetical Species | data.frame | 2823 | 12 |
ecospat.testNiche.nat | ecospat | Test Data For The Niche Dynamics Analysis In The Native Range Of A Hypothetical Species | data.frame | 10809 | 12 |
ecospat.testNichePOSNB | ecospat | Test AVS Dataset For The Ecospat package | data.frame | 16 | 19 |
aidssi | mstate | Data from the Amsterdam Cohort Studies on HIV infection and AIDS | data.frame | 329 | 5 |
aidssi2 | mstate | Data from the Amsterdam Cohort Studies on HIV infection and AIDS | data.frame | 329 | 10 |
bmt | mstate | BMT data from Klein and Moeschberger | data.frame | 137 | 22 |
ebmt1 | mstate | Data from the European Society for Blood and Marrow Transplantation (EBMT) | data.frame | 1977 | 8 |
ebmt2 | mstate | Data from the European Society for Blood and Marrow Transplantation (EBMT) | data.frame | 8966 | 9 |
ebmt3 | mstate | Data from the European Society for Blood and Marrow Transplantation (EBMT) | data.frame | 2204 | 9 |
ebmt4 | mstate | Data from the European Society for Blood and Marrow Transplantation (EBMT) | data.frame | 2279 | 15 |
prothr | mstate | Abnormal prothrombin levels in liver cirrhosis | msdata | 2152 | 8 |
TS | mFLICA | A simulation time series of movement coordination of 30 individuals | array | | |
osm_building_tags | getdata | OpenStreetMap building tags | character | | |
osm_common_tags | getdata | Common OpenStreetMap tags | tbl_df | 272 | 5 |
street_dir_prefixes | getdata | Street directional prefixes | tbl_df | 8 | 3 |
street_suffixes | getdata | Street suffix abbreviations | grouped_df | 206 | 3 |
gN3dist | SDPDmod | Distance between the centroids of NUTS3 regions in Germany | matrix | 401 | 401 |
usa46 | SDPDmod | Spatial weights matrix of 46 USA states | matrix | 46 | 46 |
origdata | nlmeVPC | Pharmacokinetics of Theophylline with a different schedule of time. | data.frame | 132 | 5 |
simdata | nlmeVPC | Simulation data | matrix | 132 | |
auto | olsrr | Test Data Set | tbl_df | 74 | 11 |
cement | olsrr | Test Data Set | data.frame | 13 | 6 |
fitness | olsrr | Test Data Set | data.frame | 31 | 7 |
hsb | olsrr | Test Data Set | data.frame | 200 | 15 |
rivers | olsrr | Test Data Set | data.frame | 20 | 6 |
stepdata | olsrr | Test Data Set | data.frame | 20000 | 7 |
surgical | olsrr | Surgical Unit Data Set | data.frame | 54 | 9 |
glottolog | qlcData | Glottolog data from <https://glottolog.org> | data.frame | 22004 | 10 |
ndvi_ts | Rwtss | Example time series from MOD13Q1 product. | wtss | 1 | 7 |
data_exprs | tidyheatmaps | Expression data from RNA-Seq study | tbl_df | 800 | 9 |
keys_d2 | d2r | D2 Syntax Keywords | list | | |
themes_d2 | d2r | D2 Themes | numeric | | |
World | evolMap | World country polygons | sf | 177 | 11 |
locations | evolMap | Data: Birthplaces locations of classical sociologists. | matrix | 16 | 2 |
sociologists | evolMap | Data: Classical sociologists. | data.frame | 16 | 11 |
breastTCGA_ER | divergence | ER positive or negative status of breast tumor samples | factor | | |
breastTCGA_Group | divergence | Normal or Tumor status of breast samples | factor | | |
breastTCGA_Mat | divergence | Gene expression for 260 genes in 887 breast samples | matrix | 260 | 887 |
msigdb_Hallmarks | divergence | Cancer Hallmark gene sets from the MSigDB collection | list | | |
sample_response | newsanchor | Sample Response Object | list | | |
terms_category | newsanchor | Terms Category | data.frame | 7 | 1 |
terms_country | newsanchor | Terms Country | data.frame | 54 | 1 |
terms_language | newsanchor | Terms Language | data.frame | 14 | 1 |
terms_sources | newsanchor | Terms Sources | data.frame | 138 | 1 |
jpnprefs | jpndistrict | Prefectural informations in Japan | tbl_df | 47 | 11 |
prefecture_mesh | jpndistrict | Prefecture's meshcode | sf | 314 | 5 |
lineardata | RobustIV | lineardata | data.frame | 1445 | 12 |
mroz | RobustIV | mroz | data.frame | 428 | 22 |
nonlineardata | RobustIV | nonlineardata | data.frame | 3733 | 9 |
FILT_EMG | musclesyneRgies | Filtered EMG example | list | | |
RAW_DATA | musclesyneRgies | Raw EMG example | list | | |
SYNS | musclesyneRgies | Muscle synergies example | list | | |
act_pattern | musclesyneRgies | Single activation pattern example (30 cycles) | data.frame | 6000 | 2 |
act_patterns | musclesyneRgies | All activation patterns of one synergy example (30 cycles) | musclesyneRgies | | |
Alcohol | ssifs | Stochastic Search Inconsistency Factor Selection of brief alcohol interventions. | data.frame | 43 | 11 |
smokingcessation | ssifs | Stochastic Search Inconsistency Factor Selection of interventions for smoking cessation | data.frame | 24 | 10 |
approved | logrx | Approved packages and functions | tbl_df | 6 | 2 |
BatchData | MethylMix | BatchData data set | data.frame | 23263 | 3 |
GEcancer | MethylMix | Cancer Gene expression data of glioblastoma patients from the TCGA project | matrix | 14 | 251 |
METcancer | MethylMix | DNA methylation data from cancer tissue from glioblastoma patients from the TCGA project | matrix | 14 | 251 |
METnormal | MethylMix | DNA methylation data from normal tissue from glioblastoma patients | matrix | 14 | 4 |
ProbeAnnotation | MethylMix | ProbeAnnotation data set | data.frame | 365860 | 2 |
SNPprobes | MethylMix | SNPprobes data set | character | | |
Australia | SDLfilter | A map of Australia | data.frame | 17138 | 7 |
SandyStrait | SDLfilter | A map of Sandy Strait, Australia | data.frame | 3847 | 7 |
bathymodel | SDLfilter | Bathymetry model for Sandy Strait, Australia | stars | | |
flatback | SDLfilter | Flatback turtle tracking data | data.frame | 1020 | 4 |
tidalplane | SDLfilter | Tidal plane table for Sandy Strait, Australia | data.frame | 2 | 6 |
tidedata | SDLfilter | Tidal data for Sandy Strait, Australia | data.frame | 26351 | 3 |
turtle | SDLfilter | Green turtle tracking data | data.frame | 429 | 5 |
turtle2 | SDLfilter | Green turtle tracking data 2 | data.frame | 276 | 5 |
ud_matrix | SDLfilter | A matrix containing probability distributions of flatback turtles | matrix | 15 | |
ud_raster | SDLfilter | A list of raster data containing probability distributions of flatback turtles | list | | |
distributions | exams.forge | Distributions | data.frame | 13 | 4 |
skalenniveau | exams.forge | Skalenniveau | data.frame | 45 | 2 |
sos100 | exams.forge | Precomputed Sum of Squared Data | matrix | 381 | |
sos1000 | exams.forge | Precomputed Sum of Squared Data | matrix | 229830 | |
sos200 | exams.forge | Precomputed Sum of Squared Data | matrix | 2433 | |
sos400 | exams.forge | Precomputed Sum of Squared Data | matrix | 15533 | |
sos800 | exams.forge | Precomputed Sum of Squared Data | matrix | 118696 | |
data_dictionary_newsmap_ar | newsmap | Seed geographical dictionary in Arabic | dictionary2 | | |
data_dictionary_newsmap_de | newsmap | Seed geographical dictionary in German | dictionary2 | | |
data_dictionary_newsmap_en | newsmap | Seed geographical dictionary in English | dictionary2 | | |
data_dictionary_newsmap_es | newsmap | Seed geographical dictionary in Spanish | dictionary2 | | |
data_dictionary_newsmap_fr | newsmap | Seed geographical dictionary in French | dictionary2 | | |
data_dictionary_newsmap_he | newsmap | Seed geographical dictionary in Hebrew | dictionary2 | | |
data_dictionary_newsmap_it | newsmap | Seed geographical dictionary in Italian | dictionary2 | | |
data_dictionary_newsmap_ja | newsmap | Seed geographical dictionary in Japanese | dictionary2 | | |
data_dictionary_newsmap_pt | newsmap | Seed geographical dictionary in Portuguese | dictionary2 | | |
data_dictionary_newsmap_ru | newsmap | Seed geographical dictionary in Russian | dictionary2 | | |
data_dictionary_newsmap_tr | newsmap | Seed geographical dictionary in Turkish | dictionary2 | | |
data_dictionary_newsmap_zh_cn | newsmap | Seed geographical dictionary in Chinese (simplified) | dictionary2 | | |
data_dictionary_newsmap_zh_tw | newsmap | Seed geographical dictionary in Chinese (traditional) | dictionary2 | | |
wine | RMSDp | Wine dataset in UCI Machine Learning Repository | data.frame | 178 | 14 |
nes_econ2008 | hIRT | Public Attitudes on Economic Issues in ANES 2008 | tbl_df | 2268 | 13 |
ERCC | denoiSeq | ERCC dataset | matrix | 92 | 10 |
simdat | denoiSeq | simulated data | matrix | 750 | 10 |
EgaEnEstellaQts | hydroGOF | Ega in "Estella" (Q071), ts with daily streamflows. | zoo | | |
bastaCMRdat | BaSTA | Example of capture-mark-recapture data for BaSTA analysis. | data.frame | 500 | 25 |
bastaCMRout | BaSTA | Output from a Bayesian Survival Trajectory Analysis (BaSTA) analysis on a simulated capture-mark-recapture (CMR) dataset. | basta | | |
bastaCensDat | BaSTA | Example of census data for BaSTA analysis. | data.frame | 500 | 8 |
bastaCensOut | BaSTA | Output from a Bayesian Survival Trajectory Analysis (BaSTA) analysis on a simulated census dataset. | basta | | |
GBP | GARCHSK | GBP/USD exchange rate from 1990-01-03 to 2002-5-3 from Bloomberg. | numeric | | |
horse_mesh | stelfi | Example Delaunay triangulation | fm_mesh_2d | | |
horse_sf | stelfi | Example 'sf' 'POLYGON' | sfc_POLYGON | | |
iraq_terrorism | stelfi | Terrorism in Iraq, 2013 - 2017 | sf | 4208 | 17 |
marked | stelfi | Example marked point pattern data set | data.frame | 159 | 5 |
multi_hawkes | stelfi | Example multivariate Hawkes dataset | data.frame | 213 | 2 |
nz_earthquakes | stelfi | Earthquakes in Canterbury, NZ, 2010 - 2014 | sf | 3824 | 4 |
nz_murders | stelfi | Murders of NZ, 2004 - 2019 | sf | 967 | 12 |
retweets_niwa | stelfi | Retweets of NIWA's viral leopard seal Tweet | POSIXct | | |
sasquatch | stelfi | Sasquatch (bigfoot) sightings in the USA, 2000 - 2005 | sf | 972 | 28 |
uk_serial | stelfi | Serial killers of the UK, 1828 - 2015 | data.frame | 62 | 8 |
xyt | stelfi | Self-exciting point pattern | stppp | | |
human_datasets | MainExistingDatasets | Human datasets | data.frame | 68 | 15 |
MUGAmaps | mmconvert | Array annotation information for the mouse MUGA arrays in mouse genome build 39. | list | | |
coxmap | mmconvert | Mouse genetic map based on Cox et al. doi:10.1534/genetics.109.105486 <https://doi.org/10.1534/genetics.109.105486>, revised for mouse genome build 39. | data.frame | 10172 | 6 |
grcm39_chrlen | mmconvert | Mouse chromosome lengths in basepairs for build GRCm39 | integer | | |
YAN | OTclust | Single cell gene data from Yan's paper | matrix | 124 | |
sim1 | OTclust | Simulated toy data | list | | |
vis_pollen | OTclust | Single cell gene visualization data from Pollen's paper | list | | |
covid_fit_df | promor | Suvarna et al 2021 LFQ data (fit object) | MArrayLM | | |
covid_norm_df | promor | Suvarna et al 2021 LFQ data (normalized) | matrix | 230 | 35 |
ecoli_fit_df | promor | Cox et al 2014 LFQ data (fit object) | MArrayLM | | |
ecoli_norm_df | promor | Cox et al 2014 LFQ data (normalized) | matrix | 4360 | 6 |
dataCar | actuaRE | data Car | data.table | 67566 | 15 |
hachemeisterLong | actuaRE | Hachemeister Data Set | data.frame | 60 | 5 |
district_age_median | pragr | Median age by district | tbl_df | 1539 | 4 |
district_age_structure | pragr | District population by age and sex | tbl_df | 29241 | 6 |
district_geofacet | pragr | Dataset to be used in the geofacet package | data.frame | 57 | 4 |
district_hexogram | pragr | Equal-area hexogram of Prague districts | sf | 57 | 12 |
district_names | pragr | Table of several variants of each districts names, with code | data.frame | 57 | 6 |
district_tilegram | pragr | Equal-area tilegram of Prague districts | sf | 57 | 12 |
prg_bbox_krovak | pragr | Prague bbox in EPSG 5514 (Krovak) | bbox | | |
prg_bbox_wgs84 | pragr | Prague bbox in EPSG 4326 (WGS 84) | bbox | | |
prg_endpoints | pragr | IPR Map Services | tbl_df | 18 | 5 |
prg_fua_oecd | pragr | Prague code in OECD database of Functional Urban Areas | character | | |
prg_ico | pragr | Prague ICO code | character | | |
prg_kod | pragr | Prague RUIAN code | character | | |
prg_kraj | pragr | Prague 'kraj' code | character | | |
prg_lau1 | pragr | Prague LAU1 code | character | | |
prg_metro_oecd | pragr | Prague code in OECD CITIES database of data on Functional Urban Areas | character | | |
prg_nuts2 | pragr | Prague NUTS2 code | character | | |
prg_nuts3 | pragr | Prague NUTS3 code | character | | |
prg_okres | pragr | Prague 'okres' code | character | | |
prg_okres_nuts | pragr | Prague 'okres LAU' code | character | | |
enron | idm | enron data set | data.frame | 39861 | 80 |
tweet | idm | twitter data set | data.frame | 7296 | 3 |
women | idm | women data set | data.frame | 2107 | 12 |
Data | toolStability | Wheat APSIM model simulated database | data.frame | 640 | 8 |
fourpl_df | PP | Simulated data set | data.frame | 60 | 14 |
pp_amt | PP | Adaptive Matrices Test data | list | | |
exData | ContRespPP | Example Continuous Response ANOVA Dataset. | matrix | 80 | 14 |
brca | AdaSampling | Wisconsin Breast Cancer Database (1991) | data.frame | 683 | 10 |
data_p | IMIX | P value matrix of two data types | matrix | 1000 | 2 |
imp20000 | RFlocalfdr | 20000 importance values | list | | |
example_course_import | crsra | Example Import of a Coursera Course | coursera_course_import | | |
tabdesc | crsra | Table Descriptions | character | | |
posters | ggimg | Movie Posters from Animated Films | spec_tbl_df | 50 | 11 |
faahko_sub | xcms | LC-MS preprocessing result test data sets | XCMSnExp | | |
faahko_sub2 | xcms | LC-MS preprocessing result test data sets | XcmsExperiment | | |
xdata | xcms | LC-MS preprocessing result test data sets | XCMSnExp | | |
xmse | xcms | LC-MS preprocessing result test data sets | XcmsExperiment | | |
abr1 | mt | abr1 Data | list | | |
CellCycle | secure | Cell cycle data | list | | |
DLBCL | secure | Chemotherapy data | list | | |
Firm | robustbetareg | Firm Cost | data.frame | 73 | 7 |
HIC | robustbetareg | Health Insurance Coverage | data.frame | 80 | 4 |
M1 | FuzzyStatTraEOO | 69 trapezoidal fuzzy numbers. | data.frame | 69 | 4 |
M2 | FuzzyStatTraEOO | 69 trapezoidal fuzzy numbers. | data.frame | 69 | 4 |
M3 | FuzzyStatTraEOO | 69 trapezoidal fuzzy numbers. | data.frame | 69 | 4 |
S1 | FuzzyStatTraEOO | 69 trapezoidal fuzzy numbers. | data.frame | 69 | 4 |
southkorea_covid19 | gwzinbr | South Korea COVID-19 dataset | tbl_df | 244 | 11 |
example_matrix | psborrow2 | Example data matrix | matrix | 500 | 11 |
example_surv | psborrow2 | Simulated Survival Data | data.frame | 600 | 8 |
cars | symbolicDA | real data set in symbolic form - selected car models described by a set of symbolic variables | symbolic | | |
data_symbolic | symbolicDA | Symbolic interval data | array | | |
ansur | psyntur | Anthropometric data from US Army Personnel | spec_tbl_df | 6068 | 9 |
faithfulfaces | psyntur | Faithfulness from a Photo? | tbl_df | 170 | 7 |
jobsatisfaction | psyntur | Job Satisfaction Data for Two-Way ANOVA | tbl_df | 58 | 4 |
pairedsleep | psyntur | Paired sleep data | tbl_df | 10 | 3 |
schizophrenia | psyntur | Age of Onset of Schizophrenia Data | tbl_df | 251 | 2 |
selfesteem | psyntur | Self-Esteem Score Data for One-way Repeated Measures ANOVA | tbl_df | 10 | 4 |
selfesteem2 | psyntur | Self Esteem Score Data for Two-way Repeated Measures ANOVA | tbl_df | 24 | 5 |
selfesteem2_long | psyntur | Self Esteem Score Data for Two-way Repeated Measures ANOVA: Long format | tbl_df | 72 | 4 |
test_psychometrics | psyntur | Psychometrics raw data from testing or demo purposes | tbl_df | 44 | 30 |
vizverb | psyntur | Visual versus Verbal Perception and Responses | tbl_df | 80 | 4 |
MACE | viscomp | Major Adverse Cardiovascular Event | data.frame | 22 | 13 |
nmaMACE | viscomp | Network Meta-Analysis of Major Adverse Cardiovascular Event | netmeta | | |
qpdat | quickpsy | Data set for demonstration | tbl_df | 1280 | 5 |
abalone | less | Abalone Data Set | data.frame | 4177 | 8 |
Election2005 | OutliersO3 | Election2005 data | data.frame | 299 | 70 |
malleco | LSTS | Average Araucaria Araucana Tree Ring Width | ts | | |
ar_stl_asthma | areal | Asthma in St. Louis by Census Tract, 2017 | sf | 106 | 9 |
ar_stl_race | areal | Race in St. Louis by Census Tract, 2017 | sf | 106 | 24 |
ar_stl_wards | areal | Ward Boundaries in St. Louis, 2010 | sf | 28 | 4 |
ar_stl_wardsClipped | areal | Clipped Ward Boundaries in St. Louis, 2010 | sf | 28 | 2 |
example_barcode_data | coil | Example barcode data. | data.frame | 9 | 5 |
pbo_NAR | reconstructKM | Pembrolizumab example OS NAR table - placebo arm | data.frame | 8 | 2 |
pbo_clicks | reconstructKM | Pembrolizumab example OS KM reconstruction clicks - placebo arm | data.frame | 96 | 2 |
pembro_NAR | reconstructKM | Pembrolizumab example OS NAR table - pembrolizumab arm | data.frame | 8 | 2 |
pembro_clicks | reconstructKM | Pembrolizumab example OS KM reconstruction clicks - pembrolizumab arm | data.frame | 97 | 2 |
lidar | VarReg | lidar dataset. | data.frame | 221 | 2 |
mcycle | VarReg | mcycle dataset. | data.frame | 133 | 2 |
vcf | VarReg | vcf dataset. | data.frame | 100 | 3 |
aids | cvGEE | Didanosine versus Zalcitabine in HIV Patients | data.frame | 1405 | 12 |
pbc2 | cvGEE | Mayo Clinic Primary Biliary Cirrhosis Data | data.frame | 1945 | 20 |
stockprice | timevarcorr | Daily Closing Prices of Major European Stock Indices, April 2000-December 2017 | tbl_df | 4618 | 7 |
classification_results | desirability2 | Classification results | tbl_df | 300 | 6 |
Census2016_ancestories | Census2016 | Two dimensional tables | data.table | 201600 | 4 |
Census2016_countries_of_birth | Census2016 | Two dimensional tables | data.table | 228480 | 4 |
Census2016_languages | Census2016 | Two dimensional tables | data.table | 221760 | 4 |
Census2016_n_women_by_children_ever_born | Census2016 | Two dimensional tables | data.table | 53760 | 4 |
Census2016_religions | Census2016 | Two dimensional tables | data.table | 181440 | 4 |
Census2016_wide_by_SA2_year | Census2016 | Census data by SA2 | data.table | 6720 | 43 |
dat_large | clipp | Simulated data on one family with approximately 10,000 members | data.frame | 10002 | 6 |
dat_small | clipp | Simulated data on 10 families with approximately 100 members each | data.frame | 1018 | 8 |
penet_large | clipp | A penetrance matrix relating the phenotypes in 'dat_large' to three genotypes | matrix | 10002 | |
penet_small | clipp | A penetrance matrix relating the phenotypes of 'dat_small' to three genotypes | matrix | 1018 | |
ExampleEQTLgenoData | eGST | An example of tissue-specific eQTLs genotype data. | list | | |
ExamplePhenoData | eGST | An example of phenotype data. | numeric | | |
ECNNO2 | atsalibrary | UK Atmospheric NO2 | data.frame | 9108 | 7 |
ECNmeta | atsalibrary | UK Atmospheric NO2 | data.frame | 12 | 4 |
KvichakSockeye | atsalibrary | Kvichak River SR Data | grouped_df | 54 | 5 |
MLCO2 | atsalibrary | Mauna Loa C02 measurements | data.frame | 709 | 3 |
NHTemp | atsalibrary | Northern Hemisphere land and ocean temperature anomalies | data.frame | 1620 | 2 |
chinook.month | atsalibrary | Monthly and annual Chinook salmon commercial landings | tbl_df | 1188 | 7 |
chinook.year | atsalibrary | Monthly and annual Chinook salmon commercial landings | data.frame | 402 | 6 |
covs | atsalibrary | Annual Anchovy, Sardine and Mackerel landings in Hellenic Waters 1964-2007 | list | | |
covsmean.mon | atsalibrary | Annual Anchovy, Sardine and Mackerel landings in Hellenic Waters 1964-2007 | data.frame | 656 | 7 |
covsmean.year | atsalibrary | Annual Anchovy, Sardine and Mackerel landings in Hellenic Waters 1964-2007 | data.frame | 55 | 6 |
greeklandings | atsalibrary | Annual Anchovy, Sardine and Mackerel landings in Hellenic Waters 1964-2007 | data.frame | 264 | 4 |
hourlyphyto | atsalibrary | Hourly phytoplankton | data.frame | 168 | 1 |
lakeWA | atsalibrary | Lake Washington Plankton Data | data.frame | 396 | 25 |
neon_barc | atsalibrary | Lake Barco Aquatic Data | tbl_df | 1254 | 11 |
snotel | atsalibrary | Washington State SNOTEL measurements | data.frame | 27720 | 6 |
snotelmeta | atsalibrary | Washington State SNOTEL measurements | data.frame | 70 | 8 |
sockeye | atsalibrary | Bristol Bay Sockeye Spawner-Recruit Data | grouped_df | 426 | 6 |
Quantile09 | mnt | Simulated empirical 90% quantiles of the tests contained in package 'mnt' | matrix | 9 | 20 |
Quantile095 | mnt | Simulated empirical 95% quantiles of the tests contained in package 'mnt' | matrix | 9 | 20 |
Quantile099 | mnt | Simulated empirical 99% quantiles of the tests contained in package 'mnt' | matrix | 9 | 20 |
sub_R25 | omXplore | Feature example data | MultiAssayExperiment | | |
vdata | omXplore | Feature example data | MultiAssayExperiment | | |
SAEval_example | SAEval | Example dataset for the evaluation of Small Area Estimates | data.frame | 107 | 18 |
sa_shp | SAEval | Example dataset to map Small Area Estimates | sf | 107 | 13 |
QTLmarkers | GALLO | Candidate markers identified by GWAS associated with fertility traits in cattle | data.frame | 141 | 7 |
QTLwindows | GALLO | Candidate windows identified by GWAS associated with fertility traits in cattle | data.frame | 50 | 8 |
gffQTLs | GALLO | A gff example for QTL annotation | data.frame | 59600 | 6 |
gtfGenes | GALLO | A gtf example for gene annotation | data.frame | 17831 | 8 |
sMIDUS | causal.decomp | Synthetic Data Generated Based on the Midlife Development in the U.S. (MIDUS) Study | data.frame | 1948 | 9 |
sdata | causal.decomp | Synthetic Data for Illustration | data.frame | 1000 | 9 |
met | GRNNs | meteorological dataset | data.frame | 378 | 11 |
physg | GRNNs | physiognomy dataset | data.frame | 378 | 31 |
data_air | gmgm | Beijing air quality dataset | tbl_df | 7680 | 6 |
data_body | gmgm | NHANES body composition dataset | tbl_df | 2148 | 8 |
gmbn_body | gmgm | Gaussian mixture Bayesian network learned from the NHANES body composition dataset | gmbn | | |
gmdbn_air | gmgm | Gaussian mixture dynamic Bayesian network learned from the Beijing air quality dataset | gmdbn | | |
gmm_body | gmgm | Gaussian mixture model learned from the NHANES body composition dataset | gmm | | |
X | WLogit | Example of a design matrix of a logistic model | matrix | 100 | |
beta | WLogit | True coefficients in the esample. | numeric | | |
test | WLogit | WLogit output | list | | |
y | WLogit | Example of a binary response variable of a logistic model. | integer | | |
X_dgp3 | RCTS | The dataset X_dgp3 contains the values of the 3 observable variables on which Y_dgp3 is based. | array | | |
Y_dgp3 | RCTS | Y_dgp3 contains a simulated dataset for DGP 3. | matrix | 300 | |
df_results_example | RCTS | An example for df_results. This dataframe contains the estimators for each configuration. | data.frame | 4 | 11 |
factor_group_true_dgp3 | RCTS | factor_group_true_dgp3 contains the values of the true group factors on which Y_dgp3 is based | list | | |
g_true_dgp3 | RCTS | g_true_dgp3 contains the true group memberships of the elements of Y_dgp3 | numeric | | |
lambda_group_true_dgp3 | RCTS | lambda_group_true_dgp3 contains the values of the loadings to the group factors on which Y_dgp3 is based | data.frame | 300 | 5 |
ELEnet16 | ITNr | Electrical Automotive Goods 2016 Network | igraph | | |
ELEnetList | ITNr | List of Electrical Automotive Goods Networks (2006-2016) | list | | |
cap_lat_lon | ITNr | cap_lat_lon | data.frame | 230 | 5 |
mutSigData | mutSignatures | Input Data and Examples for Running Mutational Signatures Analyses | list | | |
deck | bootwar | Deck of Cards | data.frame | 52 | 4 |
rnaseq | MGLM | RNA-seq count data | data.frame | 200 | 10 |
caers | openEBGM | Dietary supplement reports and products | data.frame | 20156 | 4 |
caers_raw | openEBGM | Raw CAERS data | data.frame | 117 | 6 |
NYburg | aoristic | Residential burglaries, Manhattan borough, New York City, NY, 2019 | data.frame | 1233 | 6 |
dcburglaries | aoristic | Burglaries, Washington DC, first six months of 2016 | data.frame | 1025 | 4 |
dcburgsum | aoristic | Summary output from aoristic analysis of DC burglaries | data.frame | 24 | 8 |
imports85 | RRF | The Automobile Data | data.frame | 205 | 26 |
cardiacsurgery | spcadjust | Cardiac surgery data | data.frame | 5595 | 5 |
stopwordsISO | morestopwords | Combined stop words for all languages | list | | |
c17_example | ismtchile | Datos de ejemplo, censo 2017 || || Example data, 2017 census (Chile) | data.frame | 7512 | 60 |
dataIRSN5D | DiceEval | 5D benchmark from nuclear criticality safety assessments | data.frame | 50 | 6 |
testIRSN5D | DiceEval | A set of test data | data.frame | 324 | 6 |
lucaDat | luca | Simulated data for a hypothetical binary trait | data.frame | 1000 | 4 |
nzffdr_data | nzffdr | Sample NZFFD data. | data.frame | 200 | 67 |
nzffdr_nzmap | nzffdr | Simple features map of New Zealand | sf | 4 | 2 |
esDiff | eLNNpairedCov | An ExpressionSet Object Storing a Simulated Data | ExpressionSet | | |
annotations | FAMT | Gene annotations data frame | data.frame | 9893 | 6 |
covariates | FAMT | Covariates data frame | data.frame | 43 | 6 |
expression | FAMT | Gene expressions data frame | data.frame | 9893 | 43 |
plantGrowth | Dasst | An example of a Dasst object | Dasst | | |
EEG_leadingV | bootSVD | Leading 5 Principal Components (PCs) from EEG dataset | matrix | 900 | |
EEG_mu | bootSVD | Functional mean from EEG dataset | numeric | | |
EEG_score_var | bootSVD | Empirical variance of the first 5 score variables from EEG dataset | numeric | | |
covid.cases | covid19srilanka | Covid-19 Cases by Type (Confirmed, Recovered, Death) | tbl_df | 2200 | 3 |
district.wise.cases | covid19srilanka | Covid-19 District-wise Confirmed Cases in Sri Lanka | spec_tbl_df | 832 | 3 |
vaccination | covid19srilanka | Covid-19 Vaccination Counts in Sri Lanka | spec_tbl_df | 471 | 4 |
milk | Ake | Average daily fat yields. | data.frame | 35 | 2 |
dem | PanelMatch | County-level Democracy indicator | data.frame | 9384 | 5 |
vrc01 | vimp | Neutralization sensitivity of HIV viruses to antibody VRC01 | data.frame | 611 | 837 |
moid_traits | ctpm | Trait data on 57 species of extant musteloids. | data.frame | 48 | 11 |
musteloids | ctpm | Musteloidea phylogeny. | phylo | | |
c57_nos2KO_mouse_countDF | omu | c57b6J nos2KO metabolomics count matrix | data.frame | 668 | 31 |
c57_nos2KO_mouse_metadata | omu | c57b6J nos2KO meta data | data.frame | 29 | 4 |
BR_jps_out | MultiATSM | Replications of the JPS (2014) outputs by Bauer and Rudebusch (2017) | list | | |
FactorsGVAR | MultiATSM | Data: Risk Factors for the GVAR - Candelon and Moura (2021) | list | | |
ModelPara | MultiATSM | Replications of the JPS (2014) outputs by the MultiATSM package | list | | |
RiskFactors | MultiATSM | Data: Risk Factors - Candelon and Moura (2021) | matrix | 22 | 159 |
TradeFlows | MultiATSM | Data: Trade Flows - Candelon and Moura (2021) | list | | |
Yields | MultiATSM | Data: Yields - Candelon and Moura (2021) | matrix | 24 | 159 |
compas | fairness | Modified COMPAS dataset | data.frame | 6172 | 9 |
germancredit | fairness | Modified german credit dataset | data.frame | 1000 | 23 |
CDCheight | nftbart | CDC height for age growth charts | data.frame | 436 | 9 |
bmx | nftbart | NHANES 1999-2000 Body Measures and Demographics | data.frame | 3435 | 6 |
lung | nftbart | NCCTG Lung Cancer Data | data.frame | 228 | 10 |
sic_codes | edgarWebR | SIC Codes | data.frame | 1518 | 6 |
PigDisturbance | UpDown | Non-observable information about the disturbances occuring in the 'PigFarming' dataset | data.frame | 6000 | 12 |
PigFarming | UpDown | Simulated longitudinal phenotypes that mimics a pig-farming dataset subsected to disturbances | data.frame | 578847 | 6 |
B3 | klaR | West German Business Cycles 1955-1994 | data.frame | 157 | 14 |
GermanCredit | klaR | Statlog German Credit | data.frame | 1000 | 21 |
countries | klaR | Socioeconomic data for the most populous countries. | data.frame | 42 | 7 |
freehmsData | ordgam | Perception of gay men and lesbians in Wallonia, Belgium. | data.frame | 552 | 4 |
freehmsDataBE | ordgam | Perception of gay men and lesbians in Belgium. | data.frame | 1737 | 5 |
BMIsum | gJLS2 | GIANT summary statistics for body mass index | data.frame | 100 | 5 |
chrXdat | gJLS2 | X-chromosomal example using the 1000 Genomes Project data | data.frame | 473 | 11 |
funCCdata | FunCC | Simulated data | array | | |
BM86.data | BsMD | Data sets in Box and Meyer (1986) | data.frame | 16 | 19 |
BM93.e1.data | BsMD | Example 1 data in Box and Meyer (1993) | data.frame | 12 | 7 |
BM93.e2.data | BsMD | Example 2 data in Box and Meyer (1993) | data.frame | 12 | 8 |
BM93.e3.data | BsMD | Example 3 data in Box and Meyer (1993) | data.frame | 20 | 10 |
PB12Des | BsMD | 12-run Plackett-Burman Design Matrix | data.frame | 12 | 11 |
Reactor.data | BsMD | Reactor Experiment Data | data.frame | 32 | 6 |
test_cpr | cprr | CPR numbers for testing. | tbl_df | 30 | 3 |
employment | descstat | French employment survey | tbl_df | 1000 | 7 |
padova | descstat | Housing prices in Padova | tbl_df | 1042 | 10 |
rgp | descstat | Extract of the French census | tbl_df | 1000 | 4 |
wages | descstat | DADS survey | tbl_df | 1000 | 6 |
macacaCorrel | EMMLi | Correlation matrix for 61 landmarks from Japanese macaque (_Macaca fuscata_) craniums. | data.frame | 61 | 61 |
macacaModels | EMMLi | Models of (_Macaca fuscata_) cranial modularity. | data.frame | 61 | 8 |
lhds | ergmharris | Local Health Department communication network data | network | | |
Epusillus | lhmixr | Etmopterus pusillus data | data.frame | 518 | 5 |
Espinax | lhmixr | Etmopterus spinax data | data.frame | 733 | 5 |
breastc | BcDiag | Gene Expression Data Example | matrix | 1213 | 97 |
dlbcl | BcDiag | Gene Expression Data Example | matrix | 661 | 141 |
route_data_ex | tbsa | Example Route Data | data.frame | 9 | 16 |
clt_theme_dark | colt | | colt_theme | | |
clt_theme_light | colt | | colt_theme | | |
scmixology_lib10 | FLAMES | scMixology short-read gene counts - sample 2 | SingleCellExperiment | | |
scmixology_lib10_transcripts | FLAMES | scMixology long-read transcript counts - sample 2 | SingleCellExperiment | | |
scmixology_lib90 | FLAMES | scMixology short-read gene counts - sample 1 | SingleCellExperiment | | |
LOD | EPT | Length of Day Data | list | | |
SolarRadiation | EPT | Solar Radiation | data.frame | 696 | 4 |
rice_qtl | clusterhap | Real experimental data | data.frame | 326 | 38 |
sim_qtl | clusterhap | simple QTL simulated | data.frame | 5 | 8 |
Example | MetaSKAT | Example dataset | list | | |
fredr_endpoints | fredr | List of available FRED API endpoints. | tbl_df | 31 | 3 |
anderson | psfmi | Data from a placebo-controlled RCT with leukemia patients | tbl_df | 42 | 5 |
aortadis | psfmi | Dataset of patients with a aortadissection | tbl_df | 226 | 10 |
bmd | psfmi | Data of a non-experimental study in more than 300 elderly women | tbl_df | 348 | 5 |
chlrform | psfmi | Data about concentration of ß2-microglobuline in urine as indicator for possible damage to the kidney | tbl_df | 30 | 5 |
chol_long | psfmi | Long dataset of persons from the The Amsterdam Growth and Health Longitudinal Study (AGHLS) | tbl_df | 588 | 7 |
chol_wide | psfmi | Wide dataset of persons from the The Amsterdam Growth and Health Longitudinal Study (AGHLS) | tbl_df | 147 | 12 |
day2_dataset4_mi | psfmi | Dataset of low back pain patients with missing values | tbl_df | 100 | 8 |
hipstudy | psfmi | Dataset of elderly patients with a hip fracture | tbl_df | 426 | 18 |
hipstudy_external | psfmi | External Dataset of elderly patients with a hip fracture | tbl_df | 381 | 17 |
hoorn_basic | psfmi | Dataset of the Hoorn Study | tbl_df | 250 | 12 |
infarct | psfmi | Data of a patient-control study regarding the relationship between MI and smoking | tbl_df | 420 | 10 |
ipdna_md | psfmi | Example dataset for the psfmi_mm function | data.frame | 13390 | 13 |
lbp_orig | psfmi | Example dataset for psfmi_perform function, method boot_MI | tbl_df | 159 | 15 |
lbpmi_extval | psfmi | Example dataset of Low Back Pain Patients for external validation | data.frame | 400 | 17 |
lbpmicox | psfmi | Example dataset for psfmi_coxr function | data.frame | 2650 | 18 |
lbpmilr | psfmi | Example dataset for psfmi_lr function | data.frame | 1590 | 17 |
lbpmilr_dev | psfmi | Example dataset for mivalext_lr function | data.frame | 108 | 16 |
lungvolume | psfmi | Data of the development of lung and heartvolume of unborn babies | tbl_df | 152 | 6 |
mammaca | psfmi | Data of a study among women with breast cancer | tbl_df | 1207 | 9 |
men | psfmi | Data of 613 patients with meningitis | tbl_df | 613 | 7 |
sbp_age | psfmi | Dataset with blood pressure measurements | tbl_df | 30 | 3 |
sbp_qas | psfmi | Dataset with blood pressure measurements | tbl_df | 32 | 5 |
smoking | psfmi | Survival data about smoking | tbl_df | 20 | 3 |
weight | psfmi | Dataset of persons from the The Amsterdam Growth and Health Longitudinal Study (AGHLS) | tbl_df | 450 | 7 |
exampleExpressionMatrix | fgsea | Example of expression values obtained for GSE14308. | matrix | 10000 | 12 |
examplePathways | fgsea | Example list of mouse Reactome pathways. | list | | |
exampleRanks | fgsea | Example vector of gene-level statistics obtained for Th1 polarization. | numeric | | |
PhenoarchDat1 | statgenHTP | Greenhouse data for a maize experiment in the PhenoArch platform. | data.frame | 40573 | 12 |
PhenovatorDat1 | statgenHTP | Growth chamber data for an Arabidopsis experiment in the Phenovator platform. | data.frame | 103839 | 10 |
RootDat1 | statgenHTP | Greenhouse data for an experiment in the RootPhAir platform. | data.frame | 16275 | 10 |
noCorrectedRoot | statgenHTP | Root data corrected for outliers for single observations. | data.frame | 15934 | 10 |
spatCorrectedArch | statgenHTP | Maize data corrected for spatial trends. | data.frame | 40573 | 10 |
spatCorrectedVator | statgenHTP | Arabidopsis data corrected for spatial trends. | data.frame | 103801 | 13 |
spatPredArch | statgenHTP | Maize data, genotypic predictions. | data.frame | 5940 | 6 |
TumourMethDatasets | methodical | TumourMethDatasets | data.frame | 5 | 11 |
hg38_cpgs_subset | methodical | hg38_cpgs_subset | GRanges | | |
infinium_450k_probe_granges_hg19 | methodical | infinium_450k_probe_granges_hg19 | GRanges | | |
tubb6_correlation_plot | methodical | tubb6_correlation_plot | gg | | |
tubb6_cpg_meth_transcript_cors | methodical | tubb6_cpg_meth_transcript_cors | data.frame | 355 | 5 |
tubb6_meth_rse | methodical | tubb6_meth_rse | call | | |
tubb6_tmrs | methodical | tubb6_tmrs | GRanges | | |
tubb6_transcript_counts | methodical | tubb6_transcript_counts | data.frame | 1 | 126 |
tubb6_tss | methodical | tubb6_tss | GRanges | | |
sepsis | aVirtualTwins | Clinical Trial for Sepsis desease | data.frame | 470 | 13 |
est001 | mapbayr | Estimation object | mapbayests | | |
aces_daily | JWileymisc | Multilevel Daily Data Example | data.frame | 6599 | 19 |
lob.data | obAnalytics | Example limit order book data. | list | | |
HR_data | rSAFE | Why are our best and most experienced employees leaving prematurely? | data.frame | 14999 | 10 |
apartments | rSAFE | Apartments data | data.frame | 1000 | 6 |
apartmentsTest | rSAFE | Apartments data | data.frame | 9000 | 6 |
actot | addb | Mortality and population data | demogdata | | |
aus.fertility | addb | Australian fertility data | demogdata | | |
australia | addb | Mortality and population data | demogdata | | |
nsw | addb | Mortality and population data | demogdata | | |
nt | addb | Mortality and population data | demogdata | | |
qld | addb | Mortality and population data | demogdata | | |
sa | addb | Mortality and population data | demogdata | | |
tas | addb | Mortality and population data | demogdata | | |
vic | addb | Mortality and population data | demogdata | | |
wa | addb | Mortality and population data | demogdata | | |
Ghana_2021_school_attendance | rGhanaCensus | Ghana School Attendance Indicator data | tbl_df | 64 | 10 |
Ghana_2021_school_attendance_geometry | rGhanaCensus | Ghana School Attendance Indicator data plus geometry | data.frame | 64 | 11 |
dataca20 | OBASpatial | Calcium Content In Soil Samples. | data.frame | 178 | 5 |
dataelev | OBASpatial | Surface elevations | data.frame | 52 | 3 |
geo_afstemningsomraader | dagirlite | Data from the DAGI API | sf | 1383 | 24 |
geo_kommuner | dagirlite | Data from the DAGI API | sf | 99 | 19 |
geo_postnumre | dagirlite | Data from the DAGI API | sf | 1069 | 10 |
geo_regioner | dagirlite | Data from the DAGI API | sf | 5 | 16 |
geo_sogne | dagirlite | Data from the DAGI API | sf | 2141 | 17 |
kom_tabel | dagirlite | Data to change data from old county codes to new ones, from 2007 | tbl_df | 271 | 5 |
std_kommuner | dagirlite | Data from DST for age and gender standardization on county level | tbl_df | 19962 | 4 |
std_sogne | dagirlite | Data from DST for age and gender standardization on Parrish level | tbl_df | 364479 | 4 |
artists | arthistory | Artists by edition of Gardner or Janson's art history textbook | spec_tbl_df | 3162 | 14 |
worksgardner | arthistory | Works of art from Gardner’s Art Through the Ages from 1926 until 2020 | tbl_df | 2325 | 24 |
worksjanson | arthistory | Works of art from Janson's History of Art from 1963 until 2011 | tbl_df | 1634 | 25 |
LaLonde | nawtilus | LaLonde data set | data.frame | 3212 | 12 |
ahp | r02pro | Ames Housing Price data. | spec_tbl_df | 2048 | 56 |
gm | r02pro | Gapminder Global Health Data. | tbl_df | 65531 | 33 |
gm2004 | r02pro | Gapminder Global Health Data in year 2004. | tbl_df | 472 | 23 |
sahp | r02pro | Small Version of Ames Housing Price data. | tbl_df | 165 | 12 |
E_CALORIES_FINAL | metaggR | Data: Calorie Counts | list | | |
E_CALORIES_INITIAL | metaggR | Data: Calorie Counts | list | | |
E_COINS_NESTED | metaggR | Data: Coin Flips | list | | |
E_COINS_NESTED_SYMMETRIC | metaggR | Data: Coin Flips | list | | |
E_COINS_SYMMETRIC | metaggR | Data: Coin Flips | list | | |
E_GK_1 | metaggR | Data: General Knowledge Statements | list | | |
E_GK_2 | metaggR | Data: General Knowledge Statements | list | | |
E_GK_3 | metaggR | Data: General Knowledge Statements | list | | |
E_GK_4 | metaggR | Data: General Knowledge Statements | list | | |
E_GK_5 | metaggR | Data: General Knowledge Statements | list | | |
E_GROCERIES | metaggR | Data: Grocery Prices | list | | |
E_NCAA_R16 | metaggR | Data: NCAA Basketball | list | | |
E_NCAA_R64 | metaggR | Data: NCAA Basketball | list | | |
ID_CALORIES | metaggR | Data: Calorie Counts | list | | |
ID_COINS_NESTED | metaggR | Data: Coin Flips | list | | |
ID_COINS_NESTED_SYMMETRIC | metaggR | Data: Coin Flips | list | | |
ID_COINS_SYMMETRIC | metaggR | Data: Coin Flips | list | | |
ID_GK_1 | metaggR | Data: General Knowledge Statements | list | | |
ID_GK_2 | metaggR | Data: General Knowledge Statements | list | | |
ID_GK_3 | metaggR | Data: General Knowledge Statements | list | | |
ID_GK_4 | metaggR | Data: General Knowledge Statements | list | | |
ID_GK_5 | metaggR | Data: General Knowledge Statements | list | | |
ID_GROCERIES | metaggR | Data: Grocery Prices | list | | |
ID_NCAA_R16 | metaggR | Data: NCAA Basketball | list | | |
ID_NCAA_R64 | metaggR | Data: NCAA Basketball | list | | |
P_CALORIES | metaggR | Data: Calorie Counts | list | | |
P_COINS_NESTED | metaggR | Data: Coin Flips | list | | |
P_COINS_NESTED_SYMMETRIC | metaggR | Data: Coin Flips | list | | |
P_COINS_SYMMETRIC | metaggR | Data: Coin Flips | list | | |
P_GK_1 | metaggR | Data: General Knowledge Statements | list | | |
P_GK_2 | metaggR | Data: General Knowledge Statements | list | | |
P_GK_3 | metaggR | Data: General Knowledge Statements | list | | |
P_GK_4 | metaggR | Data: General Knowledge Statements | list | | |
P_GK_5 | metaggR | Data: General Knowledge Statements | list | | |
P_GROCERIES | metaggR | Data: Grocery Prices | list | | |
P_NCAA_R16 | metaggR | Data: NCAA Basketball | list | | |
P_NCAA_R64 | metaggR | Data: NCAA Basketball | list | | |
THETA_CALORIES | metaggR | Data: Calorie Counts | integer | | |
THETA_COINS_NESTED | metaggR | Data: Coin Flips | numeric | | |
THETA_COINS_NESTED_SYMMETRIC | metaggR | Data: Coin Flips | numeric | | |
THETA_COINS_SYMMETRIC | metaggR | Data: Coin Flips | numeric | | |
THETA_GK_1 | metaggR | Data: General Knowledge Statements | integer | | |
THETA_GK_2 | metaggR | Data: General Knowledge Statements | integer | | |
THETA_GK_3 | metaggR | Data: General Knowledge Statements | integer | | |
THETA_GK_4 | metaggR | Data: General Knowledge Statements | integer | | |
THETA_GK_5 | metaggR | Data: General Knowledge Statements | integer | | |
THETA_GROCERIES | metaggR | Data: Grocery Prices | numeric | | |
THETA_NCAA_R16 | metaggR | Data: NCAA Basketball | numeric | | |
THETA_NCAA_R64 | metaggR | Data: NCAA Basketball | numeric | | |
ILsMultiple | exreport | Problem: Comparison between three Ionic Liquids packs to capture and reduce the emission of CO2 in industrial fuel combustion processes. | data.frame | 540 | 5 |
ILsPaired | exreport | Problem: Comparison between two Ionic Liquids packs to capture and reduce the emission of CO2 in industrial fuel combustion processes. | data.frame | 360 | 5 |
wekaExperiment | exreport | Problem: Comparison between several Machine Learning algorithms from the Weka library | data.frame | 1200 | 6 |
AuditC | mada | Diagnostic accuracy data | data.frame | 14 | 4 |
Dementia | mada | Diagnostic accuracy data | data.frame | 33 | 4 |
IAQ | mada | Diagnostic accuracy data | data.frame | 20 | 9 |
SAQ | mada | Diagnostic accuracy data | data.frame | 31 | 9 |
skin_tests | mada | Diagnostic accuracy data | spec_tbl_df | 10 | 4 |
smoking | mada | Diagnostic accuracy data | data.frame | 51 | 9 |
VAPort | vamc | A Randomly Generated Pool of Variable Annuities | data.frame | 19 | 45 |
cForwardCurve | vamc | Constant Forward Curve | numeric | | |
fundMap | vamc | Fund Map for 10 Funds | matrix | 10 | 5 |
histDates | vamc | Historical Scenario Dates | Date | | |
histIdxScen | vamc | Historical Index Scenario for 5 Indices over 175 Months | data.frame | 175 | 5 |
indexNames | vamc | Index Names | character | | |
indexScen | vamc | 5 Indices for 10 Scenarios over 360 Months | array | | |
mCov | vamc | Covariance Matrix for 5 Indices | matrix | 5 | |
mortTable | vamc | Mortality Rate for Male and Female from Ages 5 to 115 | data.frame | 111 | 3 |
swapRate | vamc | Swap Rates across 30 Years | numeric | | |
tc.data | DIRECT | Time-Course Microarray Gene Expression Data | data.frame | 163 | 74 |
datatest | VBTree | A test data structurized column names. | data.frame | 50 | 56 |
BigLucyT0T1 | samplesize4surveys | Some Business Population Database for two periods of time | data.frame | 170592 | 16 |
tLagData | tLagPropOdds | Toy Dataset For Illustration | data.frame | 847 | 10 |
Mena | dtp | Middle East and North Africa yearly data of economic growth, inflation rate,foreign direct investment and trade | tbl_df | 273 | 6 |
GiFACE | msaFACE | Longterm time series of a Free Air Carbon Enrichment experiment (FACE) | list | | |
simsolvd | DSBayes | Simulated SOLVD-Trial data set | data.frame | 2569 | 13 |
bread | cata | Consumer CATA data set: bread | list | | |
es | phantasus | Example dataset | ExpressionSet | | |
fgseaExample | phantasus | Example pathway data.frame for fgsea tool | data.frame | 43 | 3 |
uci_heart_failure | rtemis | UCI Heart Failure Data | data.table | 299 | 13 |
Oph | powerSurvEpi | Ophthalmology Data | data.frame | 354 | 3 |
toa_sports_keys | oddsapiR | *Sports for which odds are accessible through the Odds API* | oddsapiR_data | 77 | 5 |
anoles | ratematrix | Data and phylogenetic tree for Anolis lizards | list | | |
centrarchidae | ratematrix | Data and phylogenetic tree for Centrarchidae fishes | list | | |
decathlon2 | factoextra | Athletes' performance in decathlon | data.frame | 27 | 13 |
housetasks | factoextra | House tasks contingency table | data.frame | 13 | 4 |
multishapes | factoextra | A dataset containing clusters of multiple shapes | data.frame | 1100 | 3 |
poison | factoextra | Poison | data.frame | 55 | 15 |
HEK | directPA | Phosphoproteomics of HEK-293E | matrix | 3579 | 2 |
PM | directPA | Plasma Membrame Protoemics Data | matrix | 977 | 3 |
Pathways.KEGG | directPA | KEGG pathway annotations | list | | |
Pathways.reactome | directPA | Reactome pathway annotations | list | | |
PhosphoELM.human | directPA | PhosphoELM annotations for human | list | | |
PhosphoELM.mouse | directPA | PhosphoELM annotations for mouse | list | | |
PhosphoSite.human | directPA | PhosphoSitePlus annotations for human | list | | |
PhosphoSite.mouse | directPA | PhosphoSitePlus annotations for mouse | list | | |
pop | covid19india | List of places, abbreviations, and populations in India | data.table | 39 | 3 |
constants_table | drawsample | Fleishman's Power Method Transformation Constants | tbl_df | 5292 | 5 |
example_data | drawsample | Example Data | tbl_df | 5000 | 3 |
likert_example | drawsample | Likert Example Data | tbl_df | 6669 | 7 |
rhs_color_names_2015 | ColorNameR | UPOV names and groups for RHS colors. | tbl_df | 920 | 6 |
rhs_color_values_2007 | ColorNameR | RHS colors in different color spaces. | tbl_df | 892 | 10 |
climate_jp | clidatajp | Climate data in Japan | tbl_df | 3768 | 14 |
climate_jp_full | clidatajp | | tbl_df | 21697 | 21 |
climate_jp_full_tmp | clidatajp | | tbl_df | 21697 | 21 |
climate_world | clidatajp | Climate data in the world | tbl_df | 41328 | 12 |
japan_climate | clidatajp | Climate data in Japan | tbl_df | 3768 | 14 |
mean_cli | clidatajp | | list | | |
station_jp | clidatajp | Climate stations in Japan | tbl_df | 157 | 11 |
station_jp_full | clidatajp | | tbl_df | 1673 | 16 |
station_links | clidatajp | Station name and its URL | tbl_df | 3444 | 4 |
station_world | clidatajp | Climate stations of the world | tbl_df | 3444 | 9 |
world_climate | clidatajp | Climate data in the world | tbl_df | 41328 | 12 |
golf | integr | Golf example dataset for Interaction graphs | data.frame | 14 | 6 |
GDPmix | gfer | Table about GDP mix of China provinces in 2015 | data.table | 11 | 11 |
cm | gfer | Matrix showing complicated management of China's Water Resource | data.frame | 11 | 13 |
cancer | PairViz | Cancer Survival data | data.frame | 64 | 2 |
angiosperm_phylogeny | syntenet | Microsynteny-based angiosperm phylogeny. | phylo | | |
annotation | syntenet | Filtered genome annotation for Ostreococcus sp. species | CompressedGRangesList | | |
blast_list | syntenet | List of data frames containing BLAST-like tabular output | list | | |
clusters | syntenet | Synteny network clusters of BUSCO genes for 25 eudicot species | data.frame | 32653 | 2 |
edges | syntenet | Synteny network of Ostreococcus genomes represented as an edge list | data.frame | 1064 | 2 |
network | syntenet | Synteny network of BUSCO genes for 25 eudicot species | data.frame | 226677 | 2 |
proteomes | syntenet | Filtered proteomes of Ostreococcus sp. species | list | | |
scerevisiae_annot | syntenet | Genome annotation of the yeast species S. cerevisiae | list | | |
scerevisiae_diamond | syntenet | Intraspecies DIAMOND output for S. cerevisiae | list | | |
gwasData | gwaRs | GWAS results | data.table | 179493 | 10 |
highlightSNPS | gwaRs | Highlight SNPs | character | | |
pcaData | gwaRs | PCA results | data.table | 89 | 22 |
zeller14 | lefser | Example dataset for lefser | SummarizedExperiment | | |
olbm_dat | ordinalLBM | OLBM simulated data | list | | |
maeswrapdefinitions | Maeswrap | Example Maeswrap definition file | data.frame | 4 | 4 |
runfiletest | Maeswrap | Example Maeswrap run datafile. | data.frame | 3 | 1 |
Rdata | xlink | Simulation data for Genetic association models for X-chromosome SNPS | data.frame | 400 | 17 |
dmeladh | gggibbous | _Adh_ allele frequencies in Australasian _Drosophila melanogaster_ | data.frame | 34 | 6 |
lunardist | gggibbous | Lunar distances and principal phases for 2019 | data.frame | 365 | 3 |
ArgentinaINDEC9092F | DetLifeInsurance | ArgentinaINDEC9092 Female | data.frame | 100 | 2 |
ArgentinaINDEC9092M | DetLifeInsurance | ArgentinaINDEC9092 Male | data.frame | 100 | 2 |
ArgentinaINDEC9092comb | DetLifeInsurance | ArgentinaINDEC9092 Males and Females Combined | data.frame | 100 | 2 |
CSO2001FALBnonsmoker | DetLifeInsurance | CSO2001 Female Age Last Birthday Non-smoker | data.frame | 121 | 2 |
CSO2001FALBsmoker | DetLifeInsurance | CSO2001 Female Age Last Birthday Smoker | data.frame | 121 | 2 |
CSO2001FANBnonsmoker | DetLifeInsurance | CSO2001 Female Age Nearest Birthday Non-smoker | data.frame | 121 | 2 |
CSO2001FANBsmoker | DetLifeInsurance | CSO2001 Female Age Nearest Birthday Smoker | data.frame | 121 | 2 |
CSO2001MALBnonsmoker | DetLifeInsurance | CSO2001 Male Age Last Birthday Non-smoker | data.frame | 121 | 2 |
CSO2001MALBsmoker | DetLifeInsurance | CSO2001 Male Age Last Birthday Smoker | data.frame | 121 | 2 |
CSO2001MANBnonsmoker | DetLifeInsurance | CSO2001 Male Age Nearest Birthday Non-smoker | data.frame | 121 | 2 |
CSO2001MANBsmoker | DetLifeInsurance | CSO2001 Male Age Nearest Birthday Smoker | data.frame | 121 | 2 |
CSO58FALB | DetLifeInsurance | CSO58 Female Age Last Birthday | data.frame | 103 | 2 |
CSO58FANB | DetLifeInsurance | CSO58 Female Age Nearest Birthday | data.frame | 103 | 2 |
CSO58MALB | DetLifeInsurance | CSO58 Male Age Last Birthday | data.frame | 100 | 2 |
CSO58MANB | DetLifeInsurance | CSO58 Male Age Nearest Birthday | data.frame | 100 | 2 |
CSO80FALB | DetLifeInsurance | CSO80 Female Age Last Birthday | data.frame | 101 | 2 |
CSO80FALBnonsmoker | DetLifeInsurance | CSO80 Female Age Last Birthday non-smoker | data.frame | 100 | 2 |
CSO80FALBsmoker | DetLifeInsurance | CSO80 Female Age Last Birthday smoker | data.frame | 100 | 2 |
CSO80FANB | DetLifeInsurance | CSO80 Female Age Nearest Birthday | data.frame | 100 | 2 |
CSO80FANBnonsmoker | DetLifeInsurance | CSO80 Female Age Nearest Birthday Non-smoker | data.frame | 100 | 2 |
CSO80FANBsmoker | DetLifeInsurance | CSO80 Female Age Nearest Birthday Smoker | data.frame | 100 | 2 |
CSO80MALB | DetLifeInsurance | CSO80 Male Age Last Birthday | data.frame | 100 | 2 |
CSO80MALBnonsmoker | DetLifeInsurance | CSO80 Male Age Last Birthday Non-smoker | data.frame | 100 | 2 |
CSO80MALBsmoker | DetLifeInsurance | CSO80 Male Age Last Birthday Smoker | data.frame | 100 | 2 |
CSO80MANB | DetLifeInsurance | CSO80 Male Age Nearest Birthday | data.frame | 100 | 2 |
CSO80MANBnonsmoker | DetLifeInsurance | CSO80 Male Age Nearest Birthday Non-smoker | data.frame | 101 | 2 |
CSO80MANBsmoker | DetLifeInsurance | CSO80 Male Age Nearest Birthday Smoker | data.frame | 101 | 2 |
GAM71F | DetLifeInsurance | GAM71 Female | data.frame | 111 | 2 |
GAM71M | DetLifeInsurance | GAM71 Male | data.frame | 111 | 2 |
GAM83F | DetLifeInsurance | GAM83 Female | data.frame | 111 | 2 |
GAM83M | DetLifeInsurance | GAM83 Male | data.frame | 111 | 2 |
GAM94F | DetLifeInsurance | GAM94 Female | data.frame | 121 | 2 |
GAM94FANB | DetLifeInsurance | GAM94 Female Age Nearest Birthday | data.frame | 121 | 2 |
GAM94M | DetLifeInsurance | GAM94 Male | data.frame | 121 | 2 |
GAM94MANB | DetLifeInsurance | GAM94 Male Age Nearest Birthday | data.frame | 121 | 2 |
MAyP0206CAF | DetLifeInsurance | MAyP0206 Combined Active and Retired Female | data.frame | 116 | 2 |
MAyP0206CAM | DetLifeInsurance | MAyP0206 Combined Active and Retired Male | data.frame | 116 | 2 |
MAyP0206activeF | DetLifeInsurance | MAyP0206 Active Female | data.frame | 66 | 2 |
MAyP0206activeM | DetLifeInsurance | MAyP0206 Active Male | data.frame | 71 | 2 |
MAyP0206retiredF | DetLifeInsurance | MAyP0206 Retired Female | data.frame | 116 | 2 |
MAyP0206retiredM | DetLifeInsurance | MAyP0206 Retired Male | data.frame | 116 | 2 |
Mi06F | DetLifeInsurance | Mi06 Female | data.frame | 111 | 2 |
Mi06M | DetLifeInsurance | Mi06 Male | data.frame | 111 | 2 |
Mi85F | DetLifeInsurance | Mi85 Female | data.frame | 111 | 2 |
Mi85M | DetLifeInsurance | Mi85 Male | data.frame | 111 | 2 |
RV04F | DetLifeInsurance | RV04 Female | data.frame | 111 | 2 |
RV04M | DetLifeInsurance | RV04 Male | data.frame | 111 | 2 |
secura | ltmix | The Secura Belgian Re Data | data.frame | 371 | 2 |
cultivo2008 | baystability | Data for Genotypes by Environment Interaction (GEI) | tbl_df | 900 | 4 |
cultivo2009 | baystability | Data for Genotypes by Environment Interaction (GEI) | tbl_df | 900 | 4 |
Curitiba | NSUM | Curitiba Dataset | list | | |
McCarty | NSUM | McCarty Dataset | list | | |
funds | rportfolio | Sample Portfolio Return | xts | 901 | 2 |
veWaningData | VEwaning | Toy Dataset For Illustration | data.frame | 30000 | 8 |
ecoval.dictionaries.default | ecoval | Default Dictionaries for Nodes, Attributes and Attribute Levels | data.frame | 1159 | 9 |
msk.macrophytes.2017_ListTaxa | ecoval | Data frame containing the characteristics of the taxa to be considered for valuation. | data.frame | 390 | 17 |
msk.macrophytes.2017_RiverTypes_DefLimitsUnc | ecoval | Data frame containing the definition of uncertainty of attribute limits of river types. | data.frame | 21 | 6 |
msk.macrophytes.2017_RiverTypes_DefObsUnc | ecoval | Data frame containing the definition of observation uncertainty for river types. | data.frame | 5 | 6 |
msk.macrophytes.2017_RiverTypes_DefStruct | ecoval | Data frame containing the definition of the structure used for river types. | data.frame | 120 | 9 |
pbc | NPCox | Primary Biliary Cirrhosis data set. | data.frame | 418 | 20 |
sim_data | strata.MaxCombo | simulated survival data with two stratum | data.frame | 344 | 4 |
AIDS | gpk | AIDS Data Set | data.frame | 72 | 5 |
AirPollution | gpk | Air Pollution Data | data.frame | 151 | 11 |
AizawlCancer | gpk | Sex-wise differences in cancer types | data.frame | 19 | 3 |
Allergy | gpk | Allergy Data Set | data.frame | 7 | 4 |
Asthma1 | gpk | Testing Effect of Curcuma Longa | data.frame | 12 | 4 |
Asthma2 | gpk | Testing effect of treatment on milk induced Eosinophilia in mice | data.frame | 10 | 4 |
Asthma3 | gpk | Effect of curcuma longa on de-granulation of mast cells in mice | data.frame | 15 | 3 |
Asthma4 | gpk | Testing effect of Curcuma longa on paw inflammation in rats | data.frame | 15 | 6 |
BANK | gpk | Bank Churn data set | data.frame | 245 | 20 |
BPSYS | gpk | Two drug comparison | data.frame | 35 | 8 |
Bacteria | gpk | A multi-factorial experiment on the bacteria growth in the packaged foods | data.frame | 300 | 5 |
BambooGrowth | gpk | Data set relating growth of bamboo to geographic location | data.frame | 595 | 5 |
Bamboolife | gpk | Preparing a life table for the Bamboo plant | data.frame | 16 | 2 |
Bananabats | gpk | The Bat Census data | data.frame | 16 | 5 |
Barleyheight | gpk | Comparison of genotypes and checking time trend | data.frame | 9 | 23 |
BatGroup | gpk | Fitting distributions to the bat group size data | data.frame | 6 | 9 |
Batcapture | gpk | Understanding seasonality and species composition of bat population | data.frame | 8 | 23 |
Batrecapture | gpk | Fitting a model to bat recapture data | data.frame | 11 | 2 |
Biodegradation | gpk | Biodegradation of Dimethoate in Industrial Effluents by Brevundimonas species | data.frame | 16 | 5 |
BirthDeath | gpk | Changes in Human birth and death rates in India over the 20th century | data.frame | 27 | 3 |
Butterflies | gpk | Study of distribution of butterfly species count among 5 groups and in different localities in India | data.frame | 44 | 9 |
COWSDATA | gpk | Crossbreeding of Cows | data.frame | 10 | 7 |
Chitalparasite | gpk | Understanding the correlation of occurrence of a parasite | data.frame | 66 | 6 |
Cosmetic1 | gpk | Testing efficacy of a cosmetic product | data.frame | 48 | 3 |
Crack | gpk | Healing the heel | data.frame | 17 | 4 |
Crime | gpk | Relation between crime and intelligence | data.frame | 18 | 2 |
DroughtStress | gpk | Modeling Genotypic variation in photosynthetic competence of Sorghum bicolor | data.frame | 33 | 25 |
Dunglife | gpk | Dung decay data | data.frame | 55 | 1 |
Earthquake | gpk | Modeling earthquake aftershocks | data.frame | 121 | 10 |
EarthwormSeason | gpk | Population dynamics of earthworms | data.frame | 46 | 3 |
Earthwormbiomass | gpk | Earthworms in cultivated soils | data.frame | 12 | 5 |
Euphorbiaceae | gpk | Relationship between tree height and girth of Euphorbiaceae | data.frame | 106 | 4 |
Extruder | gpk | Understanding effect of manufacturing conditions on product characteristics | data.frame | 49 | 4 |
FAMILY | gpk | Understand relationship between height of parents and child | data.frame | 288 | 17 |
Fairness | gpk | Comparison of formulations and sample size determination of a fairness product | data.frame | 25 | 3 |
FilariasisSex | gpk | Sex related prevalence in human filariasis | data.frame | 13 | 5 |
Filariasisage | gpk | Infection among Filariasis | data.frame | 8 | 5 |
Filariasistype | gpk | Filariasis and different parasites causing it | data.frame | 13 | 5 |
Fish | gpk | Fish species interaction | data.frame | 24 | 2 |
Frog_survival | gpk | Fitting Ricker curve to frog survival data | data.frame | 8 | 2 |
Frogfood | gpk | Study of growth and food preference over age in frogs | data.frame | 7 | 6 |
Frogmating | gpk | Relation between body size and number of mates for the frogs | data.frame | 38 | 2 |
GDS | gpk | Modeling Trends in Gross Domestic Savings | data.frame | 53 | 5 |
Geometricbirds | gpk | Rank abundance distribution of bird species | data.frame | 80 | 3 |
Heart | gpk | Comparison of Test drug with Placebo for Heart Attack | data.frame | 205 | 8 |
Highjump | gpk | Guessing the gold medal score for 2004 Olympics | data.frame | 24 | 2 |
IMR | gpk | Changes in Infant mortality over last century across countries | data.frame | 6 | 5 |
IOCSharePrice | gpk | Modeling share price series of IOC | data.frame | 250 | 2 |
IslandSpArea | gpk | Species area relationship | data.frame | 16 | 2 |
Ivoryweight | gpk | Trends in illegal ivory trade | data.frame | 42 | 4 |
Lognormalbirds | gpk | Species abundance distribution | data.frame | 305 | 3 |
Logseriesbirds | gpk | Species abundance distribution | data.frame | 179 | 3 |
Loops | gpk | Loops of the finger prints | data.frame | 8 | 4 |
Lung | gpk | Smoking and Lung capacity study | data.frame | 41 | 8 |
Mammals | gpk | Birth weight and brain size of mammals | data.frame | 96 | 2 |
Mice | gpk | Protein intake and lifespan of mice | data.frame | 131 | 2 |
Microgrow | gpk | Fit sigmoidal model to bacterial growth | data.frame | 61 | 2 |
Mimosaceae | gpk | Relationship between tree height and girth | data.frame | 129 | 4 |
OralCancer | gpk | Comparison of two chemotherapy treatments for oral cancer | data.frame | 31 | 8 |
Plaque | gpk | Studying effect of toothpaste on plaque accumulation | data.frame | 60 | 3 |
Plastic | gpk | Seasonality in sales of plastic granules | data.frame | 1000 | 4 |
Poliocases | gpk | The number of polio cases | data.frame | 180 | 3 |
Preserve | gpk | Predicting fungal growth | data.frame | 60 | 4 |
Production | gpk | Quality control for examining consistency in weight | data.frame | 670 | 7 |
Pureforsure | gpk | Detection of adulteration | data.frame | 200 | 2 |
Rabbit | gpk | Relating Foot length to Body mass | data.frame | 141 | 2 |
Rat | gpk | Study of rat burrow architecture | data.frame | 6 | 4 |
RiceWheat | gpk | Modeling Rice and Wheat production | data.frame | 106 | 6 |
Sheeplife | gpk | Fitting probability distribution to life data of Sheeps | data.frame | 11 | 2 |
SholapurWeather | gpk | Has the weather in Sholapur changed over 3 decades? | data.frame | 1461 | 5 |
Sorghumheight | gpk | Modeling sorghum plant growth | data.frame | 22 | 3 |
SpaccHerb | gpk | Species accumulation curve | data.frame | 922 | 4 |
SpaccShrubs | gpk | Species accumulation curve | data.frame | 98 | 4 |
Spaceshuttle | gpk | Modeling Space shuttle O-ring failure data | data.frame | 24 | 2 |
Spareabirds | gpk | Species area curve | data.frame | 24 | 3 |
StemDensity | gpk | Vegetation types and tree density | data.frame | 11 | 9 |
TeethNormal | gpk | Modeling indicators of dental health | data.frame | 69 | 3 |
Tiger7 | gpk | Identification of individual tigers from pugmarks | data.frame | 78 | 7 |
TigerIdentity | gpk | Tiger census using scat samples | data.frame | 54 | 33 |
Timber | gpk | Genetic and environmental components of tree characteristics | data.frame | 224 | 10 |
Valvefailure | gpk | Valve characteristics and numbers of failures in a nuclear reactor | data.frame | 90 | 7 |
Waterquality | gpk | Water quality analysis using clustering | data.frame | 63 | 10 |
atombomb | gpk | Cancer deaths of atomic bomb survivors | data.frame | 42 | 4 |
birdextinct | gpk | Bird extinct at a national park | data.frame | 18 | 4 |
cloudseed | gpk | Cloud Seeding | data.frame | 52 | 2 |
elephant | gpk | Age and mating success for Elephants | data.frame | 41 | 2 |
fishtoxin | gpk | Toxicity effect on fish | data.frame | 10 | 6 |
hundredmrun | gpk | Guessing the gold medal score for 2004 Olympics | data.frame | 24 | 2 |
magazine | gpk | Time trends in authorship distribution | data.frame | 14 | 8 |
mammalsize | gpk | Correlates of brain size for the mammals | data.frame | 96 | 5 |
moth | gpk | Natural selection | data.frame | 14 | 5 |
salamander | gpk | Habitat preference of salamander | data.frame | 47 | 4 |
widowbird | gpk | Mate selection by females | data.frame | 36 | 5 |
area_unit_options | papersize | Area units (vector) | character | | |
card_sizes | papersize | Standard card sizes | tbl_df | 7 | 5 |
dist_unit_options | papersize | Distance units (vector) | character | | |
dist_units | papersize | Distance units (data frame) | tbl_df | 33 | 12 |
grid_units | papersize | Grid units (vector) | character | | |
page_extras | papersize | Extra reference data for page layouts | list | | |
paper_sizes | papersize | Standard paper and image sizes | tbl_df | 125 | 9 |
standard_scales | papersize | Standard map, architectural, and engineering scales | tbl_df | 36 | 16 |
met | inti | Swedish cultivar trial data | data.frame | 1069 | 8 |
potato | inti | Water use efficiency in 15 potato genotypes | data.frame | 150 | 17 |
dataCompoundExt | GDSARM | Compound Extraction experiment of Dopico-Garc\' ia et al. (2007) | data.frame | 12 | 9 |
dataHamadaWu | GDSARM | Cast fatigue experiment of Hunter et al. (1982) | data.frame | 12 | 8 |
ENB | HTT | Energy efficiency dataset | data.frame | 768 | 10 |
sample_Rx_processed | polypharmacy | Table: Processed _unprocessed table_ | data.table | 6744 | 4 |
sample_Rx_unprocessed | polypharmacy | Table: Prescription drugs deliveries | data.table | 17060 | 4 |
Emiliania_huxleyi | temperatureresponse | Temperature response of the growth rate of Emiliania_huxleyi | data.frame | 35 | 2 |
stock_returns | SharpeR | Stock Returns Data | xts | 4777 | 4 |
ACED.QEM | CPTtools | Data from ACED field trial | data.frame | 15 | 13 |
ACED.Qmatrix | CPTtools | Data from ACED field trial | matrix | 63 | 10 |
ACED.items | CPTtools | Data from ACED field trial | data.frame | 232 | 66 |
ACED.posttest | CPTtools | Data from ACED field trial | list | | |
ACED.prePost | CPTtools | Data from ACED field trial | data.frame | 290 | 35 |
ACED.pretest | CPTtools | Data from ACED field trial | list | | |
ACED.scores | CPTtools | Data from ACED field trial | data.frame | 230 | 66 |
ACED.skillNames | CPTtools | Data from ACED field trial | data.frame | 11 | 2 |
ACED.splitHalves | CPTtools | Data from ACED field trial | list | | |
ACED.taskNames | CPTtools | Data from ACED field trial | character | | |
Language_exp | CPTtools | Accuracy and Expected Accuracy Matrixes for Langauge Test. | list | | |
Language_modal | CPTtools | Accuracy and Expected Accuracy Matrixes for Langauge Test. | list | | |
MathGrades | CPTtools | Grades on 5 mathematics tests from Mardia, Kent and Bibby | list | | |
NYdata | spTimer | Observations of ozone concentration levels, maximum temperature and wind speed. | data.frame | 1736 | 10 |
NYgrid | spTimer | Observations of ozone concentration levels, maximum temperature and wind speed. | data.frame | 6200 | 9 |
india | RCT2 | Replication Data for: Causal Inference with Interference and Noncompliance in Two-Stage Randomized Experiments. | data.frame | 10072 | 7 |
jd | RCT2 | Replication Data for: Statistical Inference and Power Analysis for Direct and Spillover Effects in Two-Stage Randomized Experiments | data.frame | 13103 | 9 |
us_2008 | apyramid | US Census data for population, age, and gender | tbl_df | 36 | 4 |
us_2018 | apyramid | US Census data for population, age, and gender | tbl_df | 36 | 4 |
us_gen_2008 | apyramid | US Census data for population, age, and gender | tbl_df | 108 | 5 |
us_gen_2018 | apyramid | US Census data for population, age, and gender | tbl_df | 108 | 5 |
us_ins_2008 | apyramid | US Census data for population, age, and gender | tbl_df | 72 | 5 |
us_ins_2018 | apyramid | US Census data for population, age, and gender | tbl_df | 72 | 5 |
glades.env | TITAN2 | glades.env title | data.frame | 126 | 1 |
glades.taxa | TITAN2 | glades.taxa title | data.frame | 126 | 164 |
glades.titan | TITAN2 | glades.titan title | list | | |
gsubway | GSD | Seoul Subway Ridership Data | igraph | | |
ge_data | stability | Data for Genotypes by Environment Interaction (GEI) | data.frame | 1320 | 6 |
vemu | basket | Summary Data from the Vemurafenib Study | tbl_df | 18 | 6 |
vemu_wide | basket | Summary Data from the Vemurafenib Study | tbl_df | 6 | 7 |
demoFreq | wordcloud2 | Demo dataset with Words and Frequency | data.frame | 1011 | 2 |
demoFreqC | wordcloud2 | Demo dataset with Chinese character Words and Frequency | data.frame | 885 | 2 |
faux_census | fauxnaif | A small sample of a fabricated census-like dataset | spec_tbl_df | 20 | 6 |
tli | xtable | Math scores from Texas Assessment of Academic Skills (TAAS) | data.frame | 100 | 5 |
db1 | clustlearn | Test Database 1 | data.frame | 500 | 2 |
db2 | clustlearn | Test Database 2 | data.frame | 500 | 2 |
db3 | clustlearn | Test Database 3 | data.frame | 500 | 2 |
db4 | clustlearn | Test Database 4 | data.frame | 500 | 2 |
db5 | clustlearn | Test Database 5 | data.frame | 500 | 2 |
db6 | clustlearn | Test Database 6 | data.frame | 500 | 2 |
election | EffectStars2 | Election Data | data.frame | 816 | 31 |
insolvency | EffectStars2 | Insolvency data | data.frame | 1224 | 16 |
plebiscite | EffectStars2 | Chilean Plebiscite | data.frame | 2431 | 7 |
Antisemitism | cmm | Change in antisemitism after seeing a movie | data.frame | 496 | 3 |
BodySatisfaction | cmm | Body satisfaction for seven body parts | data.frame | 301 | 8 |
ClarenceThomas | cmm | Opinion on Supreme Court nominee Clarence Thomas, two-wave panel study | data.frame | 991 | 2 |
DutchConcern | cmm | Concern about crime and social security in the Netherlands | data.frame | 5742 | 3 |
DutchPolitics | cmm | Political party and candidate preference in the Netherlands | data.frame | 1100 | 4 |
EVS | cmm | European Values Study (EVS): attitude towards women's role in society | data.frame | 960 | 5 |
ErieCounty | cmm | Erie County political preference, two-wave panel | data.frame | 266 | 4 |
GSS93 | cmm | Political Orientation and Religion in the United States in 1993 (General Social Survey, 1993) | data.frame | 911 | 3 |
LaborParticipation | cmm | Women's labor participation: 1967-1971 | data.frame | 1583 | 5 |
MarihuanaAlcohol | cmm | Marihuana and alcohol use during adolescence, five-wave panel | data.frame | 269 | 11 |
NES | cmm | Political Orientation in the US, three-wave panel study | data.frame | 408 | 3 |
NKPS | cmm | Attitudes on sex roles and marriage, measurements clustered in families | data.frame | 1884 | 6 |
NKPS2 | cmm | Attitudes on sex roles and marriage, measurements clustered in families | data.frame | 1797 | 12 |
Smoking | cmm | Smoking cessation after experimental intervention | data.frame | 4144 | 6 |
TestCronbachAlpha | cmm | Testing Cronbach's alpha using marginal models | matrix | 400 | 21 |
acl | cmm | Adjective Checklist Data | matrix | 433 | 218 |
nkps1 | cmm | Attitudes on sex roles and marriage, measurements clustered in families | data.frame | 1797 | 13 |
X | SurvLong | Generated Sparse Longitudinal Data | data.frame | 400 | 3 |
Z | SurvLong | Generated Sparse Longitudinal Data | data.frame | 3237 | 3 |
Franken | MRMCaov | Multi-reader multi-case dataset | data.frame | 800 | 5 |
Kundel | MRMCaov | Multi-reader multi-case dataset | tbl_df | 1140 | 6 |
VanDyke | MRMCaov | Multi-reader multi-case dataset | data.frame | 1140 | 7 |
hospital | FEprovideR | Simulated readmissions data for 500 hospitals | data.frame | 24438 | 5 |
hospital_prepared | FEprovideR | Prepared version of simulated readmissions data for 500 hospitals | data.frame | 24438 | 8 |
faers22q3raw | pvLRT | FDA FAERS dataset for 2022 Q3 | data.table | 496312 | 3 |
gbca | pvLRT | FDA GBCA dataset with all observed 1707 adverse events | matrix | 1707 | 10 |
lovastatin | pvLRT | FDA lovastatin dataset | matrix | 47 | 3 |
rv | pvLRT | FDA rotavirus vaccine dataset with 794 adverse events observed among combined old (age >= 1 year) and young (age < 1 year) individuals | matrix | 794 | 2 |
rvold | pvLRT | FDA rotavirus vaccine dataset with 727 adverse events observed among "old" (non-infant; age >= 1 year) individuals | matrix | 727 | 2 |
rvyoung | pvLRT | FDA rotavirus vaccine dataset with 346 adverse events observed among young (infant - 1 year) individuals | matrix | 346 | 2 |
statin | pvLRT | FDA Statin dataset with 6039 adverse events | matrix | 6039 | 7 |
statin1491 | pvLRT | FDA Statin dataset with 1491 adverse events | matrix | 1491 | 7 |
statin46 | pvLRT | FDA Statin dataset with 46 adverse events | matrix | 47 | 7 |
two_class_sim_data | sparsediscrim | Example bivariate classification data from caret | tbl_df | 106 | 16 |
covid1 | AEenrich | Covid Vaccine Adverse Event Data | tbl_df | 12500 | 5 |
covid2 | AEenrich | Covid Vaccine Adverse Event Data | tbl_df | 2656 | 6 |
group | AEenrich | Group Structure Data | tbl_df | 35339 | 2 |
hospital | eventdataR | Hospital log | eventlog | 150291 | 98 |
hospital_billing | eventdataR | Hospital billing log | eventlog | 49951 | 25 |
patients | eventdataR | Patients eventlog | eventlog | 5442 | 7 |
sepsis | eventdataR | Sepsis Cases - Event Log | eventlog | 15214 | 34 |
traffic_fines | eventdataR | Road Traffic Fina Management Process Log | eventlog | 34724 | 18 |
iris_newdata | recorder | Simulated Iris New Data | data.frame | 150 | 5 |
PakPC2023Pak | PakPC2023 | Pakistan data from Pakistan Population Census 2023 | data.table | 18 | 7 |
PakPC2023PakDist | PakPC2023 | District data from Pakistan Population Census 2023 | data.table | 136 | 8 |
PakPC2023PakDiv | PakPC2023 | Divisional data from Pakistan Population Census 2023 | data.table | 31 | 7 |
example_data | Observation | Sample data collected interactively with direct observation program. | data.frame | 10 | 15 |
ERPdata | erp.easy | ERP example data | data.frame | 13530 | 23 |
stations | h3r | Stations | data.frame | 219 | 4 |
lbm | ncf | Spatio-temporal data panel of Larch Budmoth defoliation | data.frame | 135 | 40 |
SAheart | msos | South African Hearth Disease Data | data.frame | 462 | 10 |
Spam | msos | Spam | matrix | 4601 | 58 |
births | msos | Birthrates throughout the day in four Hospitals | matrix | 24 | 4 |
caffeine | msos | The Effects of Caffeine | matrix | 28 | 3 |
cars | msos | Automobile Data from Consumer Reports | matrix | 111 | 11 |
cereal | msos | Cereal | matrix | 8 | 11 |
crabs | msos | Morphological Measurements on Leptograpsus Crabs | data.frame | 200 | 8 |
decathlon08 | msos | Decathlon Event Data from 2008 Olympics. | matrix | 24 | 11 |
decathlon12 | msos | Decathlon Event Data from 2012 Olympics. | matrix | 26 | 11 |
election | msos | Presidential Election Data | matrix | 51 | 3 |
exams | msos | Statistics Students' Scores on Exams | matrix | 191 | 4 |
grades | msos | Grades | matrix | 107 | 7 |
histamine | msos | Histamine in Dogs | matrix | 16 | 4 |
leprosy | msos | Leprosy Patients | matrix | 30 | 3 |
mouths | msos | Mouth Sizes | matrix | 27 | 5 |
painters | msos | The Painter's Data of de Piles | data.frame | 54 | 5 |
planets | msos | Planets | matrix | 9 | 6 |
prostaglandin | msos | Prostaglandin | matrix | 10 | 6 |
skulls | msos | Egyptian Skulls | matrix | 150 | 5 |
softdrinks | msos | Soft Drinks | matrix | 23 | 8 |
sportsranks | msos | Sports ranking | matrix | 130 | 7 |
states | msos | States | data.frame | 51 | 11 |
baltimore_plans | baltimoredata | Baltimore City and Regional Plans | tbl_df | 354 | 36 |
city_plans | baltimoredata | | tbl_df | 314 | 36 |
entity_reference | baltimoredata | Baltimore City Entity Reference | tbl_df | 407 | 22 |
entity_xwalk | baltimoredata | Baltimore City Entity Crosswalk | tbl_df | 376 | 5 |
msa_atlas_maps | baltimoredata | Maryland State Archives Atlas Maps Index | tbl_df | 786 | 17 |
vital_signs_2010_2018 | baltimoredata | BNIA Vital Signs, 2010-2018 | tbl_df | 62552 | 6 |
vital_signs_indicators | baltimoredata | BNIA Vital Signs Indicators, 2010-2018 | tbl_df | 177 | 7 |
Argentina | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 93 | 25 |
Asia | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 98 | 39 |
Austria | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 66 | 17 |
BosniaHerz | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 63 | 17 |
China | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 67 | 71 |
Europe | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 97 | 24 |
Japan | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 82 | 71 |
USA | mispitools | STRs allelic frequencies from specified country. | spec_tbl_df | 97 | 30 |
Byiers2014 | SingleCaseES | Byiers et al., (2014) | data.frame | 54 | 9 |
Casey1978 | SingleCaseES | Casey (1978) | data.frame | 100 | 8 |
Crozier2005 | SingleCaseES | Crozier and Tincani (2015) | data.frame | 24 | 3 |
Dennis2021 | SingleCaseES | Dennis & Whalon, (2021) | data.frame | 90 | 5 |
English1997 | SingleCaseES | English, et al. (1997) | data.frame | 59 | 4 |
Facon2008 | SingleCaseES | Facon, et al. (2008) | data.frame | 49 | 4 |
Kelley2015 | SingleCaseES | Kelley et al. (2015) | data.frame | 54 | 5 |
McKissick | SingleCaseES | McKissick et al. (2010) | data.frame | 35 | 6 |
Olszewski2017 | SingleCaseES | Olszewski, et al. (2017) | data.frame | 72 | 5 |
Peters2020 | SingleCaseES | Peters-Sanders et al. (2020) | data.frame | 153 | 4 |
Schmidt2007 | SingleCaseES | Schmidt (2007) | data.frame | 172 | 13 |
Schmidt2012 | SingleCaseES | Schmidt and Stichter (2012) | data.frame | 180 | 7 |
Shogren | SingleCaseES | Shogren et al. (2004) | data.frame | 634 | 14 |
Spencer2012 | SingleCaseES | Spencer et al. (2012) | data.frame | 81 | 4 |
Strasberger2014 | SingleCaseES | Strasberger & Ferreri (2014) | data.frame | 47 | 8 |
Thorne | SingleCaseES | Thorne and Kamps (2008) | data.frame | 776 | 7 |
Wright2012 | SingleCaseES | Wright & McCathren (2012) | data.frame | 97 | 5 |
sotu_meta | sotu | Metadata from State of the Union Addresses | data.frame | 240 | 6 |
sotu_text | sotu | State of the Union Address Text | character | | |
cet_color_maps | cetcolor | RGB Value Map of the CET Perceptually Uniform Colour Maps | list | | |
MICS2014HH | PakPMICS2014HH | Multiple Indicator Cluster Survey (MICS) 2014 Household Questionnaire Data for Punjab, Pakistan | data.table | 41413 | 188 |
tu1 | vardiag | Data on Chlorid concentrations in the Suedliche Tullnerfeld | data.frame | 73 | 2 |
vs50 | vardiag | Data on Chlorid concentrations in the Suedliche Tullnerfeld | varobj | | |
Drug_MOA_Key | rcellminer | A data frame with descriptive information for all compound mechanism of action (MOA) abbreviations used in CellMiner. | data.frame | 230 | 4 |
human_gene_mapping | BPCells | Gene Symbol Mapping data | character | | |
mouse_gene_mapping | BPCells | Gene Symbol Mapping data | character | | |
AllstarFull | Lahman | AllstarFull table | data.frame | 5673 | 8 |
Appearances | Lahman | Appearances table | data.frame | 113720 | 21 |
AwardsManagers | Lahman | AwardsManagers table | data.frame | 193 | 6 |
AwardsPlayers | Lahman | AwardsPlayers table | data.frame | 6797 | 6 |
AwardsShareManagers | Lahman | AwardsShareManagers table | data.frame | 510 | 7 |
AwardsSharePlayers | Lahman | AwardsSharePlayers table | data.frame | 7447 | 7 |
Batting | Lahman | Batting table | data.frame | 113799 | 22 |
BattingPost | Lahman | BattingPost table | data.frame | 16857 | 22 |
CollegePlaying | Lahman | CollegePlaying table | data.frame | 17350 | 3 |
Fielding | Lahman | Fielding table | data.frame | 151507 | 18 |
FieldingOF | Lahman | FieldingOF table | data.frame | 12380 | 6 |
FieldingOFsplit | Lahman | FieldingOFsplit table | data.frame | 35995 | 18 |
FieldingPost | Lahman | FieldingPost data | data.frame | 16006 | 17 |
HallOfFame | Lahman | Hall of Fame Voting Data | data.frame | 6382 | 9 |
HomeGames | Lahman | HomeGames table | data.frame | 3233 | 9 |
LahmanData | Lahman | Lahman Datasets | data.frame | 27 | 5 |
Managers | Lahman | Managers table | data.frame | 3749 | 10 |
ManagersHalf | Lahman | ManagersHalf table | data.frame | 93 | 10 |
Parks | Lahman | Parks table | data.frame | 260 | 6 |
People | Lahman | People table | data.frame | 21010 | 26 |
Pitching | Lahman | Pitching table | data.frame | 51368 | 30 |
PitchingPost | Lahman | PitchingPost table | data.frame | 6757 | 30 |
Salaries | Lahman | Salaries table | data.frame | 26428 | 5 |
Schools | Lahman | Schools table | data.frame | 1241 | 5 |
SeriesPost | Lahman | SeriesPost table | data.frame | 389 | 9 |
Teams | Lahman | Teams table | data.frame | 3045 | 48 |
TeamsFranchises | Lahman | TeamFranchises table | data.frame | 120 | 4 |
TeamsHalf | Lahman | TeamsHalf table | data.frame | 52 | 10 |
battingLabels | Lahman | Variable Labels | data.frame | 22 | 2 |
fieldingLabels | Lahman | Variable Labels | data.frame | 18 | 2 |
pitchingLabels | Lahman | Variable Labels | data.frame | 30 | 2 |
simBinary | spStack | Synthetic point-referenced binary data | data.frame | 500 | 5 |
simBinom | spStack | Synthetic point-referenced binomial count data | data.frame | 500 | 6 |
simGaussian | spStack | Synthetic point-referenced Gaussian data | data.frame | 500 | 5 |
simPoisson | spStack | Synthetic point-referenced Poisson count data | data.frame | 500 | 5 |
keys | selenider | Special keys | list | | |
flowerSize | phylolm | Flower size of 25 Euphorbiaceae species | data.frame | 25 | 2 |
flowerTree | phylolm | Phylogenetic tree of 25 Euphorbiaceae species | phylo | | |
guidetree | phylolm | Binary population tree within Arabidopsis thaliana | phylo | | |
quartetCF | phylolm | Quartet concordance factors across Arabidopsis thaliana | data.frame | 27405 | 7 |
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 | 19982 | 4 |
latlong.sim.ortho.proj | cholera | Road "address" of simulated (i.e., "expected") cases (latlong). | data.frame | 19982 | 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 | | |
divipola_table | epiCo | divipola_table | data.frame | 1121 | 8 |
epi_data | epiCo | epi_data | tbl_df | 66747 | 16 |
isco88_table | epiCo | isco88_table | data.frame | 390 | 8 |
spain_ccaas | jrrosell | spain_ccaas | sf | 19 | 4 |
spain_provinces | jrrosell | spain_provinces | sf | 60 | 4 |
peru | geoperu | Distritos Peru | sf | 1874 | 4 |
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 | | |
primates | corHMM | Example datasets | list | | |
primates.paint | corHMM | Example datasets | list | | |
rayDISC.example | corHMM | Example datasets | list | | |
example_clean | ARUtools | Example cleaned recording meta data | tbl_df | 42 | 13 |
example_files | ARUtools | Example recording files | character | | |
example_files_long | ARUtools | Example long-term deployment recording files | character | | |
example_sites | ARUtools | Example site-level meta data | data.frame | 10 | 8 |
example_sites_clean | ARUtools | Example cleaned site-level meta data | tbl_df | 10 | 8 |
task_template | ARUtools | Example template of tasks for WildTrax | tbl_df | 42 | 13 |
template_observers | ARUtools | Example template of tasks for WildTrax | spec_tbl_df | 4 | 2 |
breadwheat | gosset | Preferred bread wheat varieties | tbl_df | 493 | 19 |
cassava | gosset | Gari-Eba Consumer Acceptability in Cameroon and Nigeria | data.frame | 1000 | 27 |
kenyachoice | gosset | Kenyan farmers’ preferences for agricultural and livelihood practices | list | | |
nicabean | gosset | Common bean on-farm trial in Nicaragua | list | | |
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 |
lung_FDA | mxfda | Multiplex imaging data from a non-small cell lung cancer study | mxFDA | | |
lung_df | mxfda | Multiplex imaging data from a non-small cell lung cancer study. | tbl_df | 285412 | 18 |
ovarian_FDA | mxfda | Multiplex imaging data from an ovarian cancer tumor microarray | mxFDA | | |
CPFs | moocore | Conditional Pareto fronts obtained from Gaussian processes simulations. | data.frame | 2967 | 3 |
HybridGA | moocore | Results of Hybrid GA on Vanzyl and Richmond water networks | list | | |
SPEA2minstoptimeRichmond | moocore | Results of SPEA2 when minimising electrical cost and maximising the minimum idle time of pumps on Richmond water network. | data.frame | 166 | 3 |
SPEA2relativeRichmond | moocore | Results of SPEA2 with relative time-controlled triggers on Richmond water network. | data.frame | 91 | 3 |
SPEA2relativeVanzyl | moocore | Results of SPEA2 with relative time-controlled triggers on Vanzyl's water network. | data.frame | 107 | 3 |
tpls50x20_1_MWT | moocore | Various strategies of Two-Phase Local Search applied to the Permutation Flowshop Problem with Makespan and Weighted Tardiness objectives. | data.frame | 1511 | 4 |
DivergenceExpressionSetExample | myTAI | An Example DivergenceExpressionSet Data Set | data.frame | 24132 | 9 |
PhyloExpressionSetExample | myTAI | An Example PhyloExpressionSet Data Set | data.frame | 25260 | 9 |
Rsubcapitata | cvasi | An algae scenario | AlgaeTKTDScenario | | |
Schmitt2013 | cvasi | A Lemna data set with multiple treatment levels | data.frame | 56 | 4 |
americamysis | cvasi | A DEB abj scenario of Americamysis bahia | DebAbj | | |
dmagna | cvasi | A DEBtox scenario of Daphnia magna | DebTox | | |
focusd1 | cvasi | A Lemna_SETAC scenario with variable environment | LemnaSetacScenario | | |
metsulfuron | cvasi | Lemna data published by Schmitt (2013) | LemnaSchmittScenario | | |
minnow_it | cvasi | A GUTS-RED-IT scenario of the fathead minnow | GutsRedIt | | |
minnow_sd | cvasi | A GUTS-RED-SD scenario of the fathead minnow | GutsRedSd | | |
boot.wmt | EGAnet | 'bootEGA' Results of 'wmt2'Data | bootEGA | | |
depression | EGAnet | Depression Data | data.frame | 574 | 78 |
dnn.weights | EGAnet | Loadings Comparison Test Deep Learning Neural Network Weights | list | | |
ega.wmt | EGAnet | 'EGA' Network of 'wmt2'Data | EGA | | |
intelligenceBattery | EGAnet | Intelligence Data | data.frame | 1152 | 125 |
optimism | EGAnet | Optimism Data | data.frame | 282 | 10 |
prime.num | EGAnet | Prime Numbers through 100,000 | integer | | |
sim.dynEGA | EGAnet | sim.dynEGA Data | data.frame | 5000 | 26 |
wmt2 | EGAnet | WMT-2 Data | data.frame | 1185 | 24 |
bitcoin | tscopula | Bitcoin price data 2016-19 | xts | 1044 | 1 |
cpi | tscopula | CPI inflation data 1959-2020 | xts | 245 | |
beta | fdasrvf | MPEG7 Curve Dataset | array | | |
growth_vel | fdasrvf | Berkeley Growth Velocity Dataset | list | | |
im | fdasrvf | Example Image Data set | list | | |
simu_data | fdasrvf | Simulated two Gaussian Dataset | list | | |
simu_warp | fdasrvf | Aligned Simulated two Gaussian Dataset | fdawarp | | |
simu_warp_median | fdasrvf | Aligned Simulated two Gaussian Dataset using Median | fdawarp | | |
toy_data | fdasrvf | Distributed Gaussian Peak Dataset | list | | |
toy_warp | fdasrvf | Aligned Distributed Gaussian Peak Dataset | list | | |
SFM_metric | medfate | Standard fuel models (Albini 1976, Scott & Burgan 2005) | data.frame | 53 | 18 |
SpParamsDefinition | medfate | Data tables with species parameter definitions and values | data.frame | 156 | 6 |
SpParamsMED | medfate | Data tables with species parameter definitions and values | data.frame | 217 | 157 |
exampleforest | medfate | Description of a forest stand. | forest | | |
exampleforest2 | medfate | Description of a forest stand. | forest | | |
examplemeteo | medfate | Example daily meteorology data | data.frame | 365 | 8 |
exampleobs | medfate | Example observed data | data.frame | 365 | 11 |
poblet_trees | medfate | Example forest inventory data | data.frame | 717 | 4 |
horses | tidysdm | Coordinates of radiocarbon dates for horses | tbl_df | 788 | 3 |
lacerta | tidysdm | Coordinates of presences for Iberian emerald lizard | tbl_df | 1268 | 3 |
lacerta_ensemble | tidysdm | A simple ensemble for the lacerta data | simple_ensemble | 4 | 3 |
lacerta_rep_ens | tidysdm | A repeat ensemble for the lacerta data | repeat_ensemble | 6 | 4 |
lacertidae_background | tidysdm | Coordinates of presences for lacertidae in the Iberian peninsula | tbl_df | 34677 | 3 |
mcmc.her | FLRef | | data.frame | 4997 | 328 |
ss3her | FLRef | | list | | |
divisions | nflseedR | NFL team names and the conferences and divisions they belong to | tbl_df | 36 | 4 |
foreclosure | BRcal | Foreclosure Monitoring Predictions data | data.frame | 5000 | 3 |
hockey | BRcal | Hockey Home Team Win Predictions data | data.frame | 868 | 4 |
ReineckeWell266 | copBasic | Porosity and Permeability Data for Well-266 of the Reinecke Oil Field, Horseshoe Atoll, Texas | data.frame | 235 | 6 |
ReineckeWells | copBasic | Porosity and Permeability Data for the Reinecke Oil Field, Horseshoe Atoll, Texas | data.frame | 1271 | 5 |
inflation_data | hdflex | Quarterly U.S. Inflation Dataset (Total CPI) | matrix | 245 | 462 |
example_AdmUnNames20220630 | SchoolDataIT | Subset of the administrative codes of municipalities | tbl_df | 1074 | 5 |
example_InnerAreas | SchoolDataIT | Subset of the school registry in school year 2022/23 | tbl_df | 1074 | 16 |
example_Invalsi23_prov | SchoolDataIT | Subset of the Invalsi scores in school year 2022/23 | tbl_df | 240 | 11 |
example_Prov22_shp | SchoolDataIT | Subset of Italian provinces shapefile | sf | 15 | 13 |
example_School2mun23 | SchoolDataIT | Association of the municipality code to a subset of public schools 2022/23 | list | | |
example_input_DB23_MIUR | SchoolDataIT | Subset of the school buildings database in school year 2022/23 | tbl_df | 7479 | 35 |
example_input_Registry23 | SchoolDataIT | Subset of the school registry in school year 2022/23 | tbl_df | 5929 | 10 |
example_input_nstud23 | SchoolDataIT | Subset of the students and classes counts in school year 2022/23 | tbl_df | 21208 | 7 |
eezNC | StormR | EEZ of New Caledonia | sf | 1 | 1 |
common_na_strings | cleanepi | Common strings representing missing values | character | | |
flankerData | DMCfun | A summarised dataset: This is the flanker task data from Ulrich et al. (2015) | dmcob | | |
simonData | DMCfun | A summarised dataset: This is the simon task data from Ulrich et al. (2015) | dmcob | | |
bball1970 | rstanarm | Datasets for rstanarm examples | data.frame | 18 | 5 |
bball2006 | rstanarm | Datasets for rstanarm examples | data.frame | 308 | 2 |
bcancer | rstanarm | Datasets for rstanarm examples | data.frame | 686 | 4 |
frail | rstanarm | Datasets for rstanarm examples | data.frame | 200 | 6 |
kidiq | rstanarm | Datasets for rstanarm examples | data.frame | 434 | 4 |
mice | rstanarm | Datasets for rstanarm examples | data.frame | 144 | 3 |
mortality | rstanarm | Datasets for rstanarm examples | data.frame | 12 | 2 |
pbcLong | rstanarm | Datasets for rstanarm examples | data.frame | 304 | 8 |
pbcSurv | rstanarm | Datasets for rstanarm examples | data.frame | 40 | 7 |
radon | rstanarm | Datasets for rstanarm examples | data.frame | 919 | 4 |
roaches | rstanarm | Datasets for rstanarm examples | data.frame | 262 | 5 |
tumors | rstanarm | Datasets for rstanarm examples | data.frame | 71 | 2 |
wells | rstanarm | Datasets for rstanarm examples | data.frame | 3020 | 5 |
bigdat | msmbayes | A simulated multistate dataset with lots of observations and covariates | data.frame | 36000 | 65 |
cav_misc | msmbayes | Example fitted model objects used for testing msmbayes | msmbayes | 1 | 13 |
infsim | msmbayes | Simulated infection testing data | data.frame | 3600 | 9 |
infsim2 | msmbayes | Simulated infection testing data | data.frame | 360 | 14 |
infsim_model | msmbayes | Example fitted model objects used for testing msmbayes | msmbayes | 1 | 9 |
infsim_modelc | msmbayes | Example fitted model objects used for testing msmbayes | msmbayes | 1 | 11 |
infsim_modelp | msmbayes | Example fitted model objects used for testing msmbayes | msmbayes | 1 | 8 |
infsim_modelpc | msmbayes | Example fitted model objects used for testing msmbayes | msmbayes | 1 | 9 |
gaze | eyelinkReader | Imported example.edf, events and samples | eyelinkRecording | | |
isocountry | isocountry | Country names with ISO country codes | tbl_df | 249 | 13 |
isocurrency | isocountry | ISO currency codes | tbl_df | 240 | 6 |
benchmarkData | CohortConstructor | Benchmarking results | list | | |
lung | acro | Lung Cancer Survival Data | data.frame | 228 | 10 |
nursery_data | acro | Nursery Database | data.frame | 12960 | 9 |
polymod | socialmixr | Social contact data from 8 European countries | survey | | |
Goeyvaerts | ergm.multi | A sample of within-household contact networks in Flanders and Brussels | list | | |
Lazega | ergm.multi | A network of advice, collaboration, and friendship in a law firm | network | | |
items_diao | eatATA | Small simulated item pool example. | data.frame | 165 | 5 |
items_lsa | eatATA | Simulated item pool example. | data.frame | 209 | 8 |
items_mini | eatATA | Small simulated item pool example. | data.frame | 30 | 4 |
items_pilot | eatATA | Small simulated item pool example. | data.frame | 100 | 6 |
items_vera | eatATA | Small artificial item pool example. | data.frame | 80 | 13 |
cov19incidence2022 | EpiLPS | Incidence data for Belgium in 2022 | data.frame | 540 | 6 |
cov19mort2021 | EpiLPS | Mortality data for Belgium in 2021 | data.frame | 546 | 6 |
eruptions | EpiLPS | Eruption times in Yellowstone National Park | numeric | | |
influenza2009 | EpiLPS | Data on the 2009 pandemic influenza in Pennsylvania | list | | |
sars2003 | EpiLPS | Daily incidence of the 2003 SARS epidemic in Hong Kong | list | | |
zika2015 | EpiLPS | Data on the 2015 Zika virus disease in Colombia | list | | |
Bootstrap_example | ResIN | Output example for a bootstrapping analysis conducted with the ResIN package. | list | | |
BrJSocPsychol_2024 | ResIN | Source data for Lüders, A., Carpentras, D. and Quayle, M., 2024. Attitude networks as intergroup realities: Using network‐modelling to research attitude‐identity relationships in polarized political contexts. British Journal of Social Psychology, 63(1), pp.37-51. | tbl_df | 402 | 234 |
lik_data | ResIN | Likert-type simulated data for "ResIN" package examples | data.frame | 1000 | 12 |
catalog | radiant.model | Catalog sales for men's and women's apparel | tbl_df | 200 | 5 |
direct_marketing | radiant.model | Direct marketing data | tbl_df | 1000 | 12 |
dvd | radiant.model | Data on DVD sales | tbl_df | 20000 | 5 |
houseprices | radiant.model | Houseprices | tbl_df | 128 | 6 |
ideal | radiant.model | Ideal data for linear regression | tbl_df | 1000 | 4 |
kaggle_uplift | radiant.model | Kaggle uplift | data.frame | 1000 | 22 |
ketchup | radiant.model | Data on ketchup choices | data.frame | 2798 | 14 |
movie_contract | radiant.model | Movie contract decision tree | list | | |
ratings | radiant.model | Movie ratings | tbl_df | 110 | 4 |
Pscdbp | qtlnet | Cross and qtlnet objects with Ghazalpour et al. (2006) data. Only 13 phenotypes are included. | f2 | | |
Pscdbp.bic | qtlnet | Pre-compute BIC values for qtlnet sampling. | matrix | 3887 | 3 |
Pscdbp.qtlnet | qtlnet | Cross and qtlnet objects with Ghazalpour et al. (2006) data. Only 13 phenotypes are included. | qtlnet | | |
acyclic.DG | qtlnet | Acyclic graph example | graphNEL | | |
acyclic.data | qtlnet | Acyclic graph example | f2 | | |
acyclic.qdg | qtlnet | Acyclic graph example | qdg | | |
acyclic.qtl | qtlnet | Acyclic graph example | list | | |
cyclica.data | qtlnet | Cyclic graph (a) example | f2 | | |
cyclica.qtl | qtlnet | Cyclic graph (a) example | list | | |
cyclicb.data | qtlnet | Cyclic graph (b) example | f2 | | |
cyclicb.qtl | qtlnet | Cyclic graph (b) example | list | | |
cyclicc.data | qtlnet | Cyclic graph (c) example | f2 | | |
cyclicc.qtl | qtlnet | Cyclic graph (c) example | list | | |
glxnet.cross | qtlnet | Generate and graph Glx network | f2 | | |
glxnet.qdg | qtlnet | Generate and graph Glx network | qdg | | |
glxnet.qtl | qtlnet | Generate and graph Glx network | list | | |
example.data | iCAMP | A simple example dataset for test | list | | |
icamp.out | iCAMP | Example output of function icamp.big | list | | |
data_table | drcarlate | Data used to reproduce Table 5 results in Jiang et. al. (2022) | spec_tbl_df | 2159 | 69 |
RxCdata | ei | Sample Dataset | data.frame | 60 | 6 |
census1910 | ei | Black Literacy in 1910 | data.frame | 1040 | 3 |
eiRxCsample | ei | A Sample Dataset | data.frame | 93 | 6 |
fultongen | ei | Voter Transitions | data.frame | 289 | 3 |
lavoteall | ei | Turnout by Race in Louisiana | data.frame | 3262 | 3 |
matproii | ei | Voter Registration by Race in Southern States | data.frame | 268 | 5 |
nj | ei | Nonminority Turnout in New Jersey | data.frame | 493 | 3 |
sample | ei | Sample Data for Black Votes | data.frame | 75 | 3 |
icd10_chapters | icd.data | ICD-10 chapters | list | | |
icd10_pcs | icd.data | ICD-10-CM Procedure Codes | list | | |
icd10_pcs_2014 | icd.data | ICD-10-CM Procedure Codes | data.frame | 72769 | 5 |
icd10_pcs_2015 | icd.data | ICD-10-CM Procedure Codes | data.frame | 72769 | 5 |
icd10_pcs_2016 | icd.data | ICD-10-CM Procedure Codes | data.frame | 72822 | 5 |
icd10_pcs_2017 | icd.data | ICD-10-CM Procedure Codes | data.frame | 76646 | 5 |
icd10_pcs_2018 | icd.data | ICD-10-CM Procedure Codes | data.frame | 79578 | 5 |
icd10_sub_chapters | icd.data | ICD-10 sub-chapters | list | | |
icd10cm2016 | icd.data | ICD-10-CM | data.frame | 91737 | 8 |
icd9_chapters | icd.data | ICD-9 chapters | list | | |
icd9_majors | icd.data | ICD-9 chapters | character | | |
icd9_sub_chapters | icd.data | ICD-9 chapters | list | | |
icd9cm_billable | icd.data | list of annual versions of billable leaf nodes of ICD-9-CM | list | | |
icd9cm_hierarchy | icd.data | Latest ICD-9-CM diagnosis codes, in flat 'data.frame' format | data.frame | 17561 | 8 |
uranium_pathology | icd.data | United States Transuranium & Uranium Registries | icd_long_data | 2376 | 2 |
vermont_dx | icd.data | Hospital discharge data from Vermont | icd_wide_data | 1000 | 25 |
RtDbUnits | OPI | Response times to white-on-white Goldmann Size III targets for 12 subjects in dB units | data.frame | 30620 | 3 |
RtSigmaUnits | OPI | Response times to white-on-white Goldmann Size III targets for 12 subjects in sigma units | data.frame | 30620 | 3 |
adult.data | predfairness | Adult Dataset | data.frame | 32561 | 15 |
gauss_1D_sample | PCObw | Univariate sample | numeric | | |
gauss_mD_sample | PCObw | Multivariate sample | matrix | 100 | |
Data_Maize | eemdTDNN | Monthly International Maize Price Data | ts | 228 | 1 |
X.lmer | fence | X.lmer | data.frame | 300 | 11 |
kidney | fence | kidney | data.frame | 23 | 4 |
MCZ | NPBayesImputeCat | Example dataframe for structrual zeros based on the NYMockexample dataset. | data.frame | 8 | 10 |
MCZ | NPBayesImputeCat | Example dataframe for structrual zeros based on the NYMockexample dataset. | data.frame | 60 | 10 |
X | NPBayesImputeCat | Example dataframe for input categorical data with missing values based on the NYMockexample dataset. | data.frame | 2000 | 10 |
X | NPBayesImputeCat | Example dataframe for input categorical data with missing values based on the NYMockexample dataset. | data.frame | 20000 | 10 |
ss16pusa_ds_MCZ | NPBayesImputeCat | Example dataframe for structrual zeros based on the ss16pusa_sample_zeros dataset. | data.frame | 8 | 5 |
ss16pusa_mi_MCZ | NPBayesImputeCat | Example dataframe for structrual zeros based on the ss16pusa_sample_zeros dataset. | data.frame | 8 | 5 |
ss16pusa_sample_nozeros | NPBayesImputeCat | Example dataframe for input categorical data without structural zeros (without missing values). | data.frame | 1000 | 3 |
ss16pusa_sample_nozeros_miss | NPBayesImputeCat | Example dataframe for input categorical data without structural zeros (with missing values). | data.frame | 1000 | 3 |
ss16pusa_sample_zeros | NPBayesImputeCat | Example dataframe for input categorical data with structural zeros (without missing values). | data.frame | 1000 | 5 |
ss16pusa_sample_zeros_miss | NPBayesImputeCat | Example dataframe for input categorical data with structural zeros (with missing values). | data.frame | 1000 | 5 |
spca | PCDimension | Sample PCA Dataset | SamplePCA | | |
BaitIdentityExampleFile | sfinx | A vector with proteins of interest (baits) for the TIP49 dataset. | character | | |
DataInputExampleFile | sfinx | The TIP49 dataset of protein interactions (AP-MS). | matrix | 1581 | 70 |
USA_state_N | eSIR | Population of US states | tbl_df | 52 | 2 |
confirmed | eSIR | Confirmed COVID-19 cases | spec_tbl_df | 41 | 362 |
death | eSIR | Confirmed COVID-19 deaths | spec_tbl_df | 41 | 362 |
recovered | eSIR | Confirmed COVID-19 recovered | tbl_df | 41 | 362 |
mammary | SparseTSCGM | Microarray gene expression time course data for mammary gland development in mice | longitudinal | 54 | 30 |
edgeColors | WayFindR | GPML GraphingR Data | character | | |
edgeTypes | WayFindR | GPML GraphingR Data | character | | |
nodeColors | WayFindR | GPML GraphingR Data | character | | |
nodeShapes | WayFindR | GPML GraphingR Data | character | | |
authors | GenderInfer | names dataset | data.frame | 1000 | 4 |
NCHSData | MSigSeg | influenza data set from CDC used as an example. | matrix | 52 | 10 |
T16M | MSigSeg | A chromosome sequencing data set used as an example. | data.frame | 3960 | 22 |
T16P | MSigSeg | A chromosome sequencing data set used as an example. | data.frame | 3960 | 16 |
data_test | MSigSeg | A simulated data set used for testing. | matrix | 1000 | |
stock | MSigSeg | A stock data set used as an example. | data.frame | 757 | 488 |
assets | sym.arma | Returns of the daily closing prices of assets, Standard and Poors 500 Index and T-bill rates | data.frame | 2363 | 8 |
data | DCEmgmt | Survey data from the DCE in Consumers' preferences and WTP for personalised nutrition (https://doi.org/10.1007/s40258-021-00647-3) | tbl_df | 242 | 21 |
data.c | DCEmgmt | Coded dataset | data.frame | 3744 | 20 |
design | DCEmgmt | Design matrix from the DCE in Consumers' preferences and WTP for personalised nutrition (https://doi.org/10.1007/s40258-021-00647-3) | tbl_df | 32 | 14 |
subspace_dataset | subspace | Synthetic Subspace Clustering Dataset | data.frame | 1595 | 5 |
simMetaData | metaSDTreg | Simulated metacognition experiment | data.frame | 25000 | 5 |
sockeye | bentcableAR | Rivers Inlet Sockeye Abundance | data.frame | 21 | 2 |
stagnant | bentcableAR | Stagnant Band Height Data | data.frame | 29 | 2 |
ofc | gb | OFC data | data.frame | 1000 | 2 |
Boyle | loedata | Boyle data set | data.frame | 25 | 2 |
Death | loedata | Death rate and related variables for Korean districts | data.frame | 258 | 9 |
Ekc | loedata | CO2 emissions | data.frame | 183 | 4 |
Fastfood | loedata | Card and Krueger (1994) fastfood data set | data.frame | 820 | 35 |
Firmdata | loedata | Open DART firm data | data.frame | 2073 | 23 |
Galtonpar | loedata | Galton family data | data.frame | 205 | 10 |
Hcons | loedata | Household consumption shares | data.frame | 6723 | 3 |
Hies | loedata | Household Income and Expenditure Survey 2016 | data.frame | 1368 | 26 |
Hmda | loedata | The Boston HMDA data set | data.frame | 2381 | 13 |
Ivdata | loedata | Artificial data for studying IV estimation | data.frame | 100 | 5 |
Klips | loedata | Subset of 2011 KLIPS | data.frame | 646 | 8 |
Klosa | loedata | KLoSA wave 4 | data.frame | 2153 | 45 |
Ksalary | loedata | Average salary | data.frame | 1636 | 10 |
Pubserv | loedata | Public servants and financial independence | data.frame | 86 | 3 |
Regko | loedata | Korean regional data (2014-2016 averages) | data.frame | 268 | 23 |
RegkoPanel | loedata | Korean regional panel data (2014-2016) | data.frame | 804 | 24 |
MineThatData | gains | MineThatData E-Mail Analytics Challenge Data With Predictions | data.frame | 64000 | 7 |
ciaScores | gains | Cell Phones per Country with Predictions | data.frame | 194 | 9 |
simData | plaqr | Simulated Data | data.frame | 100 | 6 |
USpopu | fANCOVA | US national population | data.frame | 320 | 3 |
dataDTWBI | DTWBI | Six univariate signals as example for DTWBI package | data.frame | 201 | 6 |
SimCml | OptimalTiming | Simulated data for CML patients | data.frame | 1777 | 14 |
ILPD | ExNRuleEnsemble | Indian Liver Patient Dataset | data.frame | 583 | 11 |
cook_creek_env | arcpullr | Various example sf polygons | sf | 10 | 3 |
cook_creek_streams | arcpullr | Various example sf polygons | sf | 5 | 3 |
cook_creek_ws | arcpullr | Various example sf polygons | sf | 1 | 7 |
example_poly | arcpullr | Various example sf polygons | sf | 1 | 1 |
iceland_poly | arcpullr | Various example sf polygons | sf | 1 | 2 |
mke_county | arcpullr | Various example sf polygons | sf | 1 | 3 |
mke_river | arcpullr | Various example sf polygons | sf | 5 | 5 |
poly_streams_contains | arcpullr | Various example sf polygons | sf | 1 | 28 |
poly_streams_crosses | arcpullr | Various example sf polygons | sf | 4 | 28 |
portage_county | arcpullr | Various example sf polygons | sf | 1 | 3 |
reykjanes_poly | arcpullr | Various example sf polygons | sf | 1 | 2 |
sp_rel_lookup | arcpullr | Spatial relationship descriptor and lookup tables | data.frame | 9 | 2 |
sp_rel_valid | arcpullr | Spatial relationship descriptor and lookup tables | tbl_df | 105 | 3 |
sugar_creek | arcpullr | Various example sf polygons | sf | 7 | 28 |
sugar_creek_env | arcpullr | Various example sf polygons | sf | 15 | 28 |
trout_hab_project_pt | arcpullr | Various example sf polygons | sf | 1 | 11 |
trout_hab_project_pts | arcpullr | Various example sf polygons | sf | 4 | 11 |
wi_aerial_imagery | arcpullr | Various example raster objects | RasterBrick | | |
wi_landcover | arcpullr | Various example raster objects | RasterLayer | | |
wis_counties | arcpullr | Various example sf polygons | sf | 72 | 3 |
wis_poly | arcpullr | Various example sf polygons | sf | 1 | 2 |
SAheart | BeSS | Risk factors associated with heart disease | data.frame | 462 | 10 |
gravier | BeSS | breast cancer data set | list | | |
prostate | BeSS | Factors associated with prostate specific antigen | data.frame | 97 | 9 |
alcohol | CVR | Data sets for the alcohol dependence example | list | | |
mouse | CVR | Data sets for the mouse body weight example | list | | |
logreg.savefit1 | LogicReg | Sample results for Logic Regression | logreg | | |
logreg.savefit2 | LogicReg | Sample results for Logic Regression | logreg | | |
logreg.savefit3 | LogicReg | Sample results for Logic Regression | logreg | | |
logreg.savefit4 | LogicReg | Sample results for Logic Regression | logreg | | |
logreg.savefit5 | LogicReg | Sample results for Logic Regression | logreg | | |
logreg.savefit6 | LogicReg | Sample results for Logic Regression | logreg | | |
logreg.savefit7 | LogicReg | Sample results for Logic Regression | logreg | | |
logreg.testdat | LogicReg | Test data for Logic Regression | matrix | 500 | |
drownings | bssm | Deaths by drowning in Finland in 1969-2019 | mts | 51 | 4 |
exchange | bssm | Pound/Dollar daily exchange rates | numeric | | |
negbin_model | bssm | Estimated Negative Binomial Model of Helske and Vihola (2021) | mcmc_output | | |
negbin_series | bssm | Simulated Negative Binomial Time Series Data | mts | 200 | 2 |
poisson_series | bssm | Simulated Poisson Time Series Data | integer | | |
appReports | shinymgr | Sample data for the shinymgr.sqlite table, "appReports" | data.frame | 3 | 3 |
appStitching | shinymgr | Sample data for the shinymgr.sqlite table, "appStitching" | data.frame | 25 | 6 |
appTabs | shinymgr | Sample data for the shinymgr.sqlite table, "appTabs" | data.frame | 12 | 3 |
apps | shinymgr | Sample data for the shinymgr.sqlite table, "apps" | data.frame | 3 | 10 |
modFunctionArguments | shinymgr | Sample data for the shinymgr.sqlite table, "modFunctionArguments" | data.frame | 6 | 5 |
modFunctionReturns | shinymgr | Sample data for the shinymgr.sqlite table, "modFunctionReturns" | data.frame | 11 | 5 |
modPackages | shinymgr | Sample data for the shinymgr.sqlite table, "modPackages" | data.frame | 9 | 4 |
modules | shinymgr | Sample data for the shinymgr.sqlite table, "modules" | data.frame | 10 | 7 |
reports | shinymgr | Sample data for the shinymgr.sqlite table, "reports" | data.frame | 3 | 3 |
tabModules | shinymgr | Sample data for the shinymgr.sqlite table, "tabModules" | data.frame | 13 | 4 |
tabs | shinymgr | Sample data for the shinymgr.sqlite table, "tabs" | data.frame | 12 | 4 |
Ysim1.5 | mcclust | Simulated 3-dimensional Normal Data Containing 8 Clusters | matrix | 400 | |
Ysim2 | mcclust | Simulated 3-dimensional Normal Data Containing 8 Clusters | matrix | 400 | |
cls.draw1.5 | mcclust | Sample of Clusterings from Posterior Distribution of Bayesian Cluster Model | matrix | 500 | 400 |
cls.draw2 | mcclust | Sample of Clusterings from Posterior Distribution of Bayesian Cluster Model | matrix | 500 | 400 |
foot | ternvis | Football betting dataset | list | | |
rain | ternvis | Ternary precipitation forecast data set | list | | |
Vehicle2 | dawai | Vehicle Silhouettes 2 | data.frame | 846 | 5 |
polio | acp | Polio cases in USA from Jan 1970 till Dec 1983 | data.frame | 168 | 1 |
finratKZ | AFR | finratKZ dataset | data.frame | 400 | 30 |
macroKZ | AFR | macroKZ dataset | mts | 57 | 60 |
nundle.sf | NCSampling | Nundle State Forest LiDAR data | data.frame | 2068 | 12 |
training | NCSampling | Nundle State Forest LiDAR data | data.frame | 200 | 10 |
hh.transmission | SIRmcmc | Simulated data under the SIR. | data.frame | 1000 | 3 |
hh.transmission.epsilon | SIRmcmc | Simulated data under SIR, with covariates. | data.frame | 2000 | 4 |
FishFC | SPEDInstabR | FACTORS AND FRESHWATER FISH SPECIES | data.frame | 7 | 22 |
Instability | SPEDInstabR | INSTABILITY INDEX AND FREQUENCIES FOR PRESENCES AND THE EXTENT | data.frame | 1530 | 15 |
VI | SPEDInstabR | CONTRIBUTION OF VEGETATION INDEX | data.frame | 181 | 361 |
adworld | SPEDInstabR | GEOGRAPHICAL COORDINATES | data.frame | 329072 | 3 |
asset.label | INFOSET | Data for clustering and labeling ETFs | spec_tbl_df | 44 | 3 |
sample.data | INFOSET | Data for infoset function | data.frame | 3174 | 44 |
sample.data.ts | INFOSET | Data with time points for portfolio construction using the LR_cp measure | data.frame | 3174 | 45 |
augusta_nlcd | landscapemetrics | Augusta NLCD 2011 | PackedSpatRaster | | |
landscape | landscapemetrics | Example map (random cluster neutral landscape model). | PackedSpatRaster | | |
lsm_abbreviations_names | landscapemetrics | Tibble of abbreviations coming from FRAGSTATS | tbl_df | 133 | 5 |
podlasie_ccilc | landscapemetrics | Podlasie ESA CCI LC | PackedSpatRaster | | |
aravo | jSDM | Distribution of Alpine plants in Aravo (Valloire, France) | list | | |
birds | jSDM | birds dataset | data.frame | 266 | 166 |
eucalypts | jSDM | eucalypts dataset | data.frame | 458 | 21 |
frogs | jSDM | frogs dataset | data.frame | 104 | 14 |
fungi | jSDM | fungi dataset | data.frame | 800 | 23 |
madagascar | jSDM | Madagascar's forest inventory | matrix | 751 | 483 |
mites | jSDM | mites dataset | data.frame | 70 | 42 |
mosquitos | jSDM | mosquitos dataset | data.frame | 167 | 31 |
starvz_sample_lu | starvz | Small StarVZ data of LU Factorization | starvz_data | | |
chickenPox | kDGLM | Hospital admissions by chicken pox in Brazil | data.frame | 120 | 6 |
cornWheat | kDGLM | Corn and wheat prices from 1986 to 2014 | data.frame | 7252 | 5 |
gastroBR | kDGLM | Hospital admissions from gastroenteritis in Brazil | tbl_df | 4212 | 4 |
noticeSARI | kDGLM | SARI data from Belo Horizonte | data.frame | 118 | 8 |
MU284pps | robsurvey | PPS Sample From the MU284 Population | data.frame | 50 | 13 |
MU284strat | robsurvey | Stratified Sample from the MU284 Population | data.frame | 60 | 14 |
counties | robsurvey | Data on a Simple Random Sample of 100 Counties in the U.S. | data.frame | 100 | 10 |
flour | robsurvey | Measurement of Copper Content in Wholemeal Flour | data.frame | 24 | 2 |
losdata | robsurvey | Length-of-Stay (LOS) Hospital Data | data.frame | 71 | 3 |
workplace | robsurvey | (Modified) Canadian Workplace and Employee Survey | data.table | 142 | 6 |
GlobalTemp | KFAS | Two series of average global temperature deviations for years 1880-1987 | mts | 108 | 2 |
alcohol | KFAS | Alcohol related deaths in Finland 1969-2013 | mts | 45 | 8 |
boat | KFAS | Oxford-Cambridge boat race results 1829-2011 | ts | | |
sexratio | KFAS | Number of males and females born in Finland from 1751 to 2011 | mts | 261 | 3 |
landsat | rsae | LANDSAT Data: Prediction of County Crop Areas Using Survey and Satellite Data | data.frame | 37 | 10 |
landsat_means | rsae | Means of the LANDSAT Data for Corn and Soybeans | data.frame | 12 | 3 |
countries | pubDashboard | List of countries taken from the package 'countrycode' | character | | |
journal_field | pubDashboard | List of academic journals and corresponding fields | tbl_df | 59 | 5 |
universities | pubDashboard | A data frame of university and corresponding country | data.frame | 9420 | 2 |
us_states | pubDashboard | List of US states taken from the package 'countrycode' | data.frame | 50 | 3 |
world_capitals | pubDashboard | List of world capitals taken from the package 'maps' | data.frame | 259 | 6 |
philips | wbacon | Philips data | matrix | 677 | 9 |
humtemp | arc | Comfort level based on temperature and humidity of the environment | data.frame | 36 | 3 |
Anolis.data | RPANDA | Anolis dataset | list | | |
BGB.examples | RPANDA | BioGeoBEARS stochastic maps | list | | |
Balaenopteridae | RPANDA | Balaenopteridae phylogeny | phylo | | |
Calomys | RPANDA | Calomys phylogeny | phylo | | |
Caprimulgidae | RPANDA | The _Caprimulgidae_ phylogeny. | phylo | | |
Caprimulgidae_ClaDS2 | RPANDA | An example run of ClaDS2. | list | | |
Cetacea | RPANDA | Cetacean phylogeny | phylo | | |
Cetacea_clades | RPANDA | Stochastic map of clade membership in Cetacean phylogeny | simmap | | |
ClaDS0_example | RPANDA | An example run of ClaDS0. | list | | |
InfTemp | RPANDA | Paleotemperature data across the Cenozoic | data.frame | 17632 | 2 |
Phocoenidae | RPANDA | Phocoenidae phylogeny | phylo | | |
Phyllostomidae | RPANDA | Phyllostomidae phylogeny | phylo | | |
Phyllostomidae_genera | RPANDA | Phylogenies of Phyllostomidae genera | list | | |
co2 | RPANDA | co2 data since the Jurassic | data.frame | 53 | 2 |
co2 | RPANDA | co2 data since the Jurassic | data.frame | 17624 | 2 |
coccolithophore | RPANDA | Coccolithophore diversity since the Jurassic | data.frame | 40 | 2 |
d13c | RPANDA | d13c data since the Jurassic | data.frame | 69 | 2 |
foraminifera | RPANDA | Foraminifera diversity since the Jurassic | data.frame | 52 | 2 |
greenalgae | RPANDA | Green algae diversity since the Jurassic | data.frame | 41 | 2 |
landplant | RPANDA | Land plant diversity since the Jurassic | data.frame | 41 | 2 |
mycorrhizal_network | RPANDA | Mycorrhizal network from La Réunion island | list | | |
ostracoda | RPANDA | Ostracod diversity since the Jurassic | data.frame | 52 | 2 |
radiolaria | RPANDA | Radiolaria diversity since the Jurassic | data.frame | 52 | 2 |
redalgae | RPANDA | Red algae diversity since the Jurassic | data.frame | 41 | 2 |
sealevel | RPANDA | Sea level data since the Jurassic | data.frame | 3161 | 2 |
shifts_cetacea | RPANDA | Cetacean shift.estimates results | list | | |
silica | RPANDA | Silica data across the Cenozoic | data.frame | 67 | 2 |
taxo_cetacea | RPANDA | Cetacean taxonomy | data.frame | 89 | 4 |
AS | RBesT | Ankylosing Spondylitis. | data.frame | 8 | 3 |
colitis | RBesT | Ulcerative Colitis. | data.frame | 4 | 3 |
crohn | RBesT | Crohn's disease. | data.frame | 6 | 3 |
transplant | RBesT | Transplant. | data.frame | 11 | 3 |
g2m.phase | iCellR | A dataset of G2 and M phase genes | character | | |
s.phase | iCellR | A dataset of S phase genes | character | | |
ebmtcal | calibmsm | European Group for Blood and Marrow Transplantation data (one row per individual) | data.frame | 2279 | 17 |
ebmtcal.cmprsk | calibmsm | European Group for Blood and Marrow Transplantation data (one row per individual) | data.frame | 2279 | 17 |
msebmtcal | calibmsm | European Group for Blood and Marrow Transplantation data in 'msdata' format. | msdata | 15512 | 8 |
msebmtcal.cmprsk | calibmsm | European Group for Blood and Marrow Transplantation data in competing risks format, for transitions out of the initial state only | msdata | 9116 | 8 |
tp.cmprsk.j0 | calibmsm | Predicted risks for a competing risks model out of state j = 0 | data.frame | 2279 | 13 |
tps0 | calibmsm | Predicted transition probabilities out of transplant state made at time s = 0 | data.frame | 13674 | 14 |
tps100 | calibmsm | Predicted transition probabilities out of every state made at time s = 100 | data.frame | 13674 | 14 |
pontzer | enerscape | Energy cost of transport from Pontzer (2016) | data.frame | 92 | 5 |
sirente | enerscape | Monte Sirente Digital Elevation Model | matrix | 393 | |
invalid_example | One4All | Invalid example data | list | | |
test_rules | One4All | Rules data | data.frame | 165 | 6 |
valid_example | One4All | Valid example data | list | | |
asset_audit | robotoolbox | Examples of KoboToolbox assets and list of assets | kobo_asset | | |
asset_list | robotoolbox | Examples of KoboToolbox assets and list of assets | tbl_df | 28 | 7 |
asset_ml | robotoolbox | Examples of KoboToolbox assets and list of assets | kobo_asset | | |
asset_rg | robotoolbox | Examples of KoboToolbox assets and list of assets | kobo_asset | | |
asset_sm_label | robotoolbox | Examples of KoboToolbox assets and list of assets | kobo_asset | | |
asset_spatial | robotoolbox | Examples of KoboToolbox assets and list of assets | kobo_asset | | |
data_audit | robotoolbox | Examples of KoboToolbox submissions data | tbl_df | 29 | 15 |
data_ml_ar | robotoolbox | Examples of KoboToolbox submissions data | tbl_df | 5 | 16 |
data_ml_default | robotoolbox | Examples of KoboToolbox submissions data | tbl_df | 5 | 16 |
data_ml_en | robotoolbox | Exa |