Showing 200 of total 4427 results (show query)
humaniverse
IMD:Index of Multiple Deprivation Data for the UK
Index of Multiple Deprivation for UK nations at various geographical levels. In England, deprivation data is for Lower Layer Super Output Areas, Middle Layer Super Output Areas, Wards, and Local Authorities based on data from <https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019>. In Wales, deprivation data is for Lower Layer Super Output Areas, Middle Layer Super Output Areas, Wards, and Local Authorities based on data from <https://gov.wales/welsh-index-multiple-deprivation-full-index-update-ranks-2019>. In Scotland, deprivation data is for Data Zones, Intermediate Zones, and Council Areas based on data from <https://simd.scot>. In Northern Ireland, deprivation data is for Super Output Areas and Local Government Districts based on data from <https://www.nisra.gov.uk/statistics/deprivation/northern-ireland-multiple-deprivation-measure-2017-nimdm2017>. The 'IMD' package also provides the composite UK index developed by <https://github.com/mysociety/composite_uk_imd>.
Maintained by Matthew Gwynfryn Thomas. Last updated 24 days ago.
105.2 match 14 stars 6.78 score 54 scripts
kbroman
qtl:Tools for Analyzing QTL Experiments
Analysis of experimental crosses to identify genes (called quantitative trait loci, QTLs) contributing to variation in quantitative traits. Broman et al. (2003) <doi:10.1093/bioinformatics/btg112>.
Maintained by Karl W Broman. Last updated 7 months ago.
39.5 match 80 stars 12.79 score 2.4k scripts 29 dependents
husson
FactoMineR:Multivariate Exploratory Data Analysis and Data Mining
Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).
Maintained by Francois Husson. Last updated 3 months ago.
30.8 match 47 stars 14.71 score 5.6k scripts 112 dependents
igraph
igraph:Network Analysis and Visualization
Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.
Maintained by Kirill Mรผller. Last updated 14 hours ago.
complex-networksgraph-algorithmsgraph-theorymathematicsnetwork-analysisnetwork-graphfortranlibxml2glpkopenblascpp
20.8 match 582 stars 21.11 score 31k scripts 1.9k dependents
tidyverse
dplyr:A Grammar of Data Manipulation
A fast, consistent tool for working with data frame like objects, both in memory and out of memory.
Maintained by Hadley Wickham. Last updated 14 days ago.
16.7 match 4.8k stars 24.68 score 659k scripts 7.8k dependents
adeverse
ade4:Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences
Tools for multivariate data analysis. Several methods are provided for the analysis (i.e., ordination) of one-table (e.g., principal component analysis, correspondence analysis), two-table (e.g., coinertia analysis, redundancy analysis), three-table (e.g., RLQ analysis) and K-table (e.g., STATIS, multiple coinertia analysis). The philosophy of the package is described in Dray and Dufour (2007) <doi:10.18637/jss.v022.i04>.
Maintained by Aurรฉlie Siberchicot. Last updated 14 days ago.
26.7 match 39 stars 14.96 score 2.2k scripts 256 dependents
cran
wavemulcor:Wavelet Routines for Global and Local Multiple Regression and Correlation
Wavelet routines that calculate single sets of wavelet multiple regressions and correlations, and cross-regressions and cross-correlations from a multivariate time series. Dynamic versions of the routines allow the wavelet local multiple (cross-)regressions and (cross-)correlations to evolve over time.
Maintained by Javier Fernandez-Macho. Last updated 4 years ago.
111.3 match 3.48 score 2 dependents
mlr-org
mlr3pipelines:Preprocessing Operators and Pipelines for 'mlr3'
Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
Maintained by Martin Binder. Last updated 10 days ago.
baggingdata-sciencedataflow-programmingensemble-learningmachine-learningmlr3pipelinespreprocessingstacking
29.9 match 141 stars 12.36 score 448 scripts 7 dependentstidyverse
tidyr:Tidy Messy Data
Tools to help to create tidy data, where each column is a variable, each row is an observation, and each cell contains a single value. 'tidyr' contains tools for changing the shape (pivoting) and hierarchy (nesting and 'unnesting') of a dataset, turning deeply nested lists into rectangular data frames ('rectangling'), and extracting values out of string columns. It also includes tools for working with missing values (both implicit and explicit).
Maintained by Hadley Wickham. Last updated 14 days ago.
14.7 match 1.4k stars 22.88 score 168k scripts 5.5k dependents
lrberge
fixest:Fast Fixed-Effects Estimations
Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) <https://github.com/lrberge/fixest/blob/master/_DOCS/FENmlm_paper.pdf>. Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.
Maintained by Laurent Berge. Last updated 7 months ago.
19.0 match 387 stars 14.69 score 3.8k scripts 25 dependents
polar-fhir
fhircrackr:Handling HL7 FHIRยฎ Resources in R
Useful tools for conveniently downloading FHIR resources in xml format and converting them to R data.frames. The package uses FHIR-search to download bundles from a FHIR server, provides functions to save and read xml-files containing such bundles and allows flattening the bundles to data.frames using XPath expressions. FHIRยฎ is the registered trademark of HL7 and is used with the permission of HL7. Use of the FHIR trademark does not constitute endorsement of this product by HL7.
Maintained by Julia Palm. Last updated 12 days ago.
36.5 match 33 stars 7.63 score 46 scripts
bioc
msa:Multiple Sequence Alignment
The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.
Maintained by Ulrich Bodenhofer. Last updated 1 months ago.
multiplesequencealignmentalignmentmultiplecomparisonsequencingcpp
23.8 match 17 stars 11.46 score 744 scripts 6 dependents
elvanceyhan
pcds:Proximity Catch Digraphs and Their Applications
Contains the functions for construction and visualization of various families of the proximity catch digraphs (PCDs) (see (Ceyhan (2005) ISBN:978-3-639-19063-2), for computing the graph invariants for testing the patterns of segregation and association against complete spatial randomness (CSR) or uniformity in one, two and three dimensional cases. The package also has tools for generating points from these spatial patterns. The graph invariants used in testing spatial point data are the domination number (Ceyhan (2011) <doi:10.1080/03610921003597211>) and arc density (Ceyhan et al. (2006) <doi:10.1016/j.csda.2005.03.002>; Ceyhan et al. (2007) <doi:10.1002/cjs.5550350106>). The PCD families considered are Arc-Slice PCDs, Proportional-Edge PCDs, and Central Similarity PCDs.
Maintained by Elvan Ceyhan. Last updated 2 years ago.
46.2 match 5.80 score 21 scripts 2 dependents
usepa
tcpl:ToxCast Data Analysis Pipeline
The ToxCast Data Analysis Pipeline ('tcpl') is an R package that manages, curve-fits, plots, and stores ToxCast data to populate its linked MySQL database, 'invitrodb'. The package was developed for the chemical screening data curated by the US EPA's Toxicity Forecaster (ToxCast) program, but 'tcpl' can be used to support diverse chemical screening efforts.
Maintained by Jason Brown. Last updated 4 days ago.
27.9 match 36 stars 9.41 score 90 scripts
emmanuelparadis
ape:Analyses of Phylogenetics and Evolution
Functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, reading and writing nucleotide sequences as well as importing from BioConductor, and several tools such as Mantel's test, generalized skyline plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation of absolute evolutionary rates and clock-like trees using mean path lengths and penalized likelihood, dating trees with non-contemporaneous sequences, translating DNA into AA sequences, and assessing sequence alignments. Phylogeny estimation can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, Muscle) whose results are returned into R.
Maintained by Emmanuel Paradis. Last updated 2 days ago.
15.2 match 64 stars 17.22 score 13k scripts 599 dependents
alexiosg
rugarch:Univariate GARCH Models
ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting.
Maintained by Alexios Galanos. Last updated 3 months ago.
21.3 match 26 stars 12.13 score 1.3k scripts 15 dependents
mjskay
ggdist:Visualizations of Distributions and Uncertainty
Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include but are not limited to: points with multiple uncertainty intervals, eye plots (Spiegelhalter D., 1999) <https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>, density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>, quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>, complementary cumulative distribution function barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>, and fit curves with multiple uncertainty ribbons.
Maintained by Matthew Kay. Last updated 4 months ago.
ggplot2uncertaintyuncertainty-visualizationvisualizationcpp
15.6 match 856 stars 15.24 score 3.1k scripts 61 dependents
openpharma
DoseFinding:Planning and Analyzing Dose Finding Experiments
The DoseFinding package provides functions for the design and analysis of dose-finding experiments (with focus on pharmaceutical Phase II clinical trials). It provides functions for: multiple contrast tests, fitting non-linear dose-response models (using Bayesian and non-Bayesian estimation), calculating optimal designs and an implementation of the MCPMod methodology (Pinheiro et al. (2014) <doi:10.1002/sim.6052>).
Maintained by Marius Thomas. Last updated 6 days ago.
23.0 match 8 stars 10.32 score 98 scripts 10 dependentscran
agricolae:Statistical Procedures for Agricultural Research
Original idea was presented in the thesis "A statistical analysis tool for agricultural research" to obtain the degree of Master on science, National Engineering University (UNI), Lima-Peru. Some experimental data for the examples come from the CIP and others research. Agricolae offers extensive functionality on experimental design especially for agricultural and plant breeding experiments, which can also be useful for other purposes. It supports planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, factorial, split and strip plot designs. There are also various analysis facilities for experimental data, e.g. treatment comparison procedures and several non-parametric tests comparison, biodiversity indexes and consensus cluster.
Maintained by Felipe de Mendiburu. Last updated 1 years ago.
30.9 match 7 stars 7.01 score 15 dependents
jcfaria
fdth:Frequency Distribution Tables, Histograms and Polygons
Perform frequency distribution tables, associated histograms and polygons from vector, data.frame and matrix objects for numerical and categorical variables.
Maintained by Josรฉ C. Faria. Last updated 1 years ago.
35.8 match 2 stars 5.87 score 107 scripts
gdemin
expss:Tables, Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics
Package computes and displays tables with support for 'SPSS'-style labels, multiple and nested banners, weights, multiple-response variables and significance testing. There are facilities for nice output of tables in 'knitr', 'Shiny', '*.xlsx' files, R and 'Jupyter' notebooks. Methods for labelled variables add value labels support to base R functions and to some functions from other packages. Additionally, the package brings popular data transformation functions from 'SPSS' Statistics and 'Excel': 'RECODE', 'COUNT', 'COUNTIF', 'VLOOKUP' and etc. These functions are very useful for data processing in marketing research surveys. Package intended to help people to move data processing from 'Excel' and 'SPSS' to R.
Maintained by Gregory Demin. Last updated 11 months ago.
excellabelslabels-supportmsexcelpivot-tablesrecodespssspss-statisticstablesvariable-labelsvlookup
18.8 match 84 stars 11.00 score 1.8k scripts 4 dependents
billdenney
PKNCA:Perform Pharmacokinetic Non-Compartmental Analysis
Compute standard Non-Compartmental Analysis (NCA) parameters for typical pharmacokinetic analyses and summarize them.
Maintained by Bill Denney. Last updated 17 days ago.
ncanoncompartmental-analysispharmacokinetics
16.3 match 73 stars 12.61 score 214 scripts 4 dependents
rdatatable
data.table:Extension of `data.frame`
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Maintained by Tyson Barrett. Last updated 13 hours ago.
8.6 match 3.7k stars 23.53 score 230k scripts 4.6k dependents
business-science
tidyquant:Tidy Quantitative Financial Analysis
Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.
Maintained by Matt Dancho. Last updated 1 months ago.
dplyrfinancial-analysisfinancial-datafinancial-statementsmultiple-stocksperformance-analysisperformanceanalyticsquantmodstockstock-exchangesstock-indexesstock-listsstock-performancestock-pricesstock-symboltidyversetime-seriestimeseriesxts
14.9 match 872 stars 13.34 score 5.2k scripts
crunch-io
crunch:Crunch.io Data Tools
The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.
Maintained by Greg Freedman Ellis. Last updated 12 days ago.
18.7 match 9 stars 10.53 score 200 scripts 2 dependents
r-lib
zeallot:Multiple, Unpacking, and Destructuring Assignment
Provides a %<-% operator to perform multiple, unpacking, and destructuring assignment in R. The operator unpacks the right-hand side of an assignment into multiple values and assigns these values to variables on the left-hand side of the assignment.
Maintained by Nathan Teetor. Last updated 5 years ago.
destructuring-assignmentmultiple-assignmentpattern-matchingunpacking-assignment
15.2 match 258 stars 12.81 score 1.9k scripts 111 dependents
harrelfe
Hmisc:Harrell Miscellaneous
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.
Maintained by Frank E Harrell Jr. Last updated 1 days ago.
11.1 match 210 stars 17.61 score 17k scripts 750 dependents
cbiit
LDlinkR:Calculating Linkage Disequilibrium (LD) in Human Population Groups of Interest
Provides access to the 'LDlink' API (<https://ldlink.nih.gov/?tab=apiaccess>) using the R console. This programmatic access facilitates researchers who are interested in performing batch queries in 1000 Genomes Project (2015) <doi:10.1038/nature15393> data using 'LDlink'. 'LDlink' is an interactive and powerful suite of web-based tools for querying germline variants in human population groups of interest. For more details, please see Machiela et al. (2015) <doi:10.1093/bioinformatics/btv402>.
Maintained by Timothy A. Myers. Last updated 11 months ago.
ld-calculatorldlinkldlink-apildlink-webtoollinkage-disequilibriumpopulation-genetics
21.1 match 58 stars 9.21 score 206 scripts 1 dependents
amices
mice:Multivariate Imputation by Chained Equations
Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.
Maintained by Stef van Buuren. Last updated 7 days ago.
chained-equationsfcsimputationmicemissing-datamissing-valuesmultiple-imputationmultivariate-datacpp
11.6 match 462 stars 16.50 score 10k scripts 154 dependents
hopkinsidd
phylosamp:Sample Size Calculations for Molecular and Phylogenetic Studies
Implements novel tools for estimating sample sizes needed for phylogenetic studies, including studies focused on estimating the probability of true pathogen transmission between two cases given phylogenetic linkage and studies focused on tracking pathogen variants at a population level. Methods described in Wohl, Giles, and Lessler (2021) and in Wohl, Lee, DiPrete, and Lessler (2023).
Maintained by Justin Lessler. Last updated 2 years ago.
28.2 match 12 stars 6.65 score 25 scripts
matthewblackwell
Amelia:A Program for Missing Data
A tool that "multiply imputes" missing data in a single cross-section (such as a survey), from a time series (like variables collected for each year in a country), or from a time-series-cross-sectional data set (such as collected by years for each of several countries). Amelia II implements our bootstrapping-based algorithm that gives essentially the same answers as the standard IP or EMis approaches, is usually considerably faster than existing approaches and can handle many more variables. Unlike Amelia I and other statistically rigorous imputation software, it virtually never crashes (but please let us know if you find to the contrary!). The program also generalizes existing approaches by allowing for trends in time series across observations within a cross-sectional unit, as well as priors that allow experts to incorporate beliefs they have about the values of missing cells in their data. Amelia II also includes useful diagnostics of the fit of multiple imputation models. The program works from the R command line or via a graphical user interface that does not require users to know R.
Maintained by Matthew Blackwell. Last updated 4 months ago.
20.7 match 1 stars 9.06 score 1.4k scripts 7 dependents
spatstat
spatstat.geom:Geometrical Functionality of the 'spatstat' Family
Defines spatial data types and supports geometrical operations on them. Data types include point patterns, windows (domains), pixel images, line segment patterns, tessellations and hyperframes. Capabilities include creation and manipulation of data (using command line or graphical interaction), plotting, geometrical operations (rotation, shift, rescale, affine transformation), convex hull, discretisation and pixellation, Dirichlet tessellation, Delaunay triangulation, pairwise distances, nearest-neighbour distances, distance transform, morphological operations (erosion, dilation, closing, opening), quadrat counting, geometrical measurement, geometrical covariance, colour maps, calculus on spatial domains, Gaussian blur, level sets of images, transects of images, intersections between objects, minimum distance matching. (Excludes spatial data on a network, which are supported by the package 'spatstat.linnet'.)
Maintained by Adrian Baddeley. Last updated 15 hours ago.
classes-and-objectsdistance-calculationgeometrygeometry-processingimagesmensurationplottingpoint-patternsspatial-dataspatial-data-analysis
15.5 match 7 stars 12.11 score 241 scripts 227 dependents
alexanderrobitzsch
miceadds:Some Additional Multiple Imputation Functions, Especially for 'mice'
Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are implemented. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>), substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>), and features for the generation of synthetic datasets (Reiter, 2005, <doi:10.1111/j.1467-985X.2004.00343.x>; Nowok, Raab, & Dibben, 2016, <doi:10.18637/jss.v074.i11>).
Maintained by Alexander Robitzsch. Last updated 17 days ago.
missing-datamultiple-imputationopenblascpp
20.2 match 16 stars 9.16 score 542 scripts 9 dependents
plangfelder
WGCNA:Weighted Correlation Network Analysis
Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.
Maintained by Peter Langfelder. Last updated 6 months ago.
18.9 match 54 stars 9.65 score 5.3k scripts 32 dependentsopenpharma
graphicalMCP:Graphical Multiple Comparison Procedures
Multiple comparison procedures (MCPs) control the familywise error rate in clinical trials. Graphical MCPs include many commonly used procedures as special cases; see Bretz et al. (2011) <doi:10.1002/bimj.201000239>, Lu (2016) <doi:10.1002/sim.6985>, and Xi et al. (2017) <doi:10.1002/bimj.201600233>. This package is a low-dependency implementation of graphical MCPs which allow mixed types of tests. It also includes power simulations and visualization of graphical MCPs.
Maintained by Dong Xi. Last updated 4 months ago.
24.8 match 17 stars 7.35 score 18 scripts
bayesiandemography
rvec:Vector Representing a Random Variable
Random vectors, called rvecs. An rvec holds multiple draws, but tries to behave like a standard R vector, including working well in data frames. Rvecs are useful for working with output from a simulation or a Bayesian analysis.
Maintained by John Bryant. Last updated 6 months ago.
32.9 match 2 stars 5.46 score 24 scripts 2 dependents
darwin-eu
DrugUtilisation:Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model
Summarise patient-level drug utilisation cohorts using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. New users and prevalent users cohorts can be generated and their characteristics, indication and drug use summarised.
Maintained by Martรญ Catalร . Last updated 2 months ago.
21.3 match 8.27 score 156 scripts 2 dependents
bozenne
LMMstar:Repeated Measurement Models for Discrete Times
Companion R package for the course "Statistical analysis of correlated and repeated measurements for health science researchers" taught by the section of Biostatistics of the University of Copenhagen. It implements linear mixed models where the model for the variance-covariance of the residuals is specified via patterns (compound symmetry, toeplitz, unstructured, ...). Statistical inference for mean, variance, and correlation parameters is performed based on the observed information and a Satterthwaite approximation of the degrees of freedom. Normalized residuals are provided to assess model misspecification. Statistical inference can be performed for arbitrary linear or non-linear combination(s) of model coefficients. Predictions can be computed conditional to covariates only or also to outcome values.
Maintained by Brice Ozenne. Last updated 5 months ago.
28.0 match 4 stars 6.28 score 141 scriptsspatstat
spatstat.model:Parametric Statistical Modelling and Inference for the 'spatstat' Family
Functionality for parametric statistical modelling and inference for spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Supports parametric modelling, formal statistical inference, and model validation. Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope tests, Dao-Genton test, balanced independent two-stage test), confidence intervals for parameters, and prediction intervals for point counts. Model validation techniques include leverage, influence, partial residuals, added variable plots, diagnostic plots, pseudoscore residual plots, model compensators and Q-Q plots.
Maintained by Adrian Baddeley. Last updated 9 days ago.
analysis-of-variancecluster-processconfidence-intervalscox-processdeterminantal-point-processesgibbs-processinfluenceleveragemodel-diagnosticsneyman-scottparameter-estimationpoisson-processspatial-analysisspatial-modellingspatial-point-processesstatistical-inference
18.9 match 5 stars 9.09 score 6 scripts 46 dependents
rpolars
polars:Lightning-Fast 'DataFrame' Library
Lightning-fast 'DataFrame' library written in 'Rust'. Convert R data to 'Polars' data and vice versa. Perform fast, lazy, larger-than-memory and optimized data queries. 'Polars' is interoperable with the package 'arrow', as both are based on the 'Apache Arrow' Columnar Format.
Maintained by Soren Welling. Last updated 4 days ago.
14.2 match 499 stars 12.01 score 1.0k scripts 2 dependents
pharmaverse
admiral:ADaM in R Asset Library
A toolbox for programming Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam>).
Maintained by Ben Straub. Last updated 5 days ago.
cdiscclinical-trialsopen-source
11.9 match 236 stars 13.89 score 486 scripts 4 dependents
markfairbanks
tidytable:Tidy Interface to 'data.table'
A tidy interface to 'data.table', giving users the speed of 'data.table' while using tidyverse-like syntax.
Maintained by Mark Fairbanks. Last updated 2 months ago.
14.4 match 458 stars 11.41 score 732 scripts 10 dependents
mikeblazanin
gcplyr:Wrangle and Analyze Growth Curve Data
Easy wrangling and model-free analysis of microbial growth curve data, as commonly output by plate readers. Tools for reshaping common plate reader outputs into 'tidy' formats and merging them with design information, making data easy to work with using 'gcplyr' and other packages. Also streamlines common growth curve processing steps, like smoothing and calculating derivatives, and facilitates model-free characterization and analysis of growth data. See methods at <https://mikeblazanin.github.io/gcplyr/>.
Maintained by Mike Blazanin. Last updated 2 months ago.
20.7 match 30 stars 7.90 score 75 scripts
mayoverse
arsenal:An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
An Arsenal of 'R' functions for large-scale statistical summaries, which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and which use formulas and versatile summary statistics for summary tables and models. The primary functions include tableby(), a Table-1-like summary of multiple variable types 'by' the levels of one or more categorical variables; paired(), a Table-1-like summary of multiple variable types paired across two time points; modelsum(), which performs simple model fits on one or more endpoints for many variables (univariate or adjusted for covariates); freqlist(), a powerful frequency table across many categorical variables; comparedf(), a function for comparing data.frames; and write2(), a function to output tables to a document.
Maintained by Ethan Heinzen. Last updated 7 months ago.
baseline-characteristicsdescriptive-statisticsmodelingpaired-comparisonsreportingstatisticstableone
12.1 match 225 stars 13.45 score 1.2k scripts 16 dependents
rich-iannone
DiagrammeR:Graph/Network Visualization
Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.
Maintained by Richard Iannone. Last updated 2 months ago.
graphgraph-functionsnetwork-graphproperty-graphvisualization
10.7 match 1.7k stars 15.18 score 3.8k scripts 87 dependents
ropensci
stantargets:Targets for Stan Workflows
Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'stantargets' R package leverages 'targets' and 'cmdstanr' to ease these burdens. 'stantargets' makes it super easy to set up scalable Stan pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. 'stantargets' can access all of 'cmdstanr''s major algorithms (MCMC, variational Bayes, and optimization) and it supports both single-fit workflows and multi-rep simulation studies. For the statistical methodology, please refer to 'Stan' documentation (Stan Development Team 2020) <https://mc-stan.org/>.
Maintained by William Michael Landau. Last updated 1 months ago.
bayesianhigh-performance-computingmaker-targetopiareproducibilitystanstatisticstargets
23.8 match 49 stars 6.85 score 180 scriptsbioc
multtest:Resampling-based multiple hypothesis testing
Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.
Maintained by Katherine S. Pollard. Last updated 5 months ago.
microarraydifferentialexpressionmultiplecomparison
17.1 match 9.34 score 932 scripts 136 dependents
kassambara
survminer:Drawing Survival Curves using 'ggplot2'
Contains the function 'ggsurvplot()' for drawing easily beautiful and 'ready-to-publish' survival curves with the 'number at risk' table and 'censoring count plot'. Other functions are also available to plot adjusted curves for `Cox` model and to visually examine 'Cox' model assumptions.
Maintained by Alboukadel Kassambara. Last updated 5 months ago.
9.7 match 524 stars 15.87 score 7.0k scripts 55 dependents
jaredlander
useful:A Collection of Handy, Useful Functions
A set of little functions that have been found useful to do little odds and ends such as plotting the results of K-means clustering, substituting special text characters, viewing parts of a data.frame, constructing formulas from text and building design and response matrices.
Maintained by Jared P. Lander. Last updated 1 years ago.
19.5 match 8 stars 7.75 score 748 scripts 6 dependents
tslumley
rimu:Responses in Multiplex
Tools for manipulating, exploring, and visualising multiple-response data, including scored or ranked responses. Conversions to and from factors, lists, strings, matrices; reordering, lumping, flattening; set operations; tables; frequency and co-occurrence plots.
Maintained by Thomas Lumley. Last updated 12 months ago.
30.5 match 4 stars 4.78 score 10 scripts
noramvillanueva
clustcurv:Determining Groups in Multiples Curves
A method for determining groups in multiple curves with an automatic selection of their number based on k-means or k-medians algorithms. The selection of the optimal number is provided by bootstrap methods. The methodology can be applied both in regression and survival framework. Implemented methods are: Grouping multiple survival curves described by Villanueva et al. (2018) <doi:10.1002/sim.8016>.
Maintained by Nora M. Villanueva. Last updated 4 months ago.
clusteringdata-analyticsmachinelearningmultiple-curvesnonparametric-statisticsnumber-of-clustersregressionsurvival-analysis
26.2 match 3 stars 5.53 score 38 scripts
kornl
gMCP:Graph Based Multiple Comparison Procedures
Functions and a graphical user interface for graphical described multiple test procedures.
Maintained by Kornelius Rohmeyer. Last updated 12 months ago.
19.9 match 10 stars 7.28 score 105 scripts 2 dependents
kassambara
factoextra:Extract and Visualize the Results of Multivariate Data Analyses
Provides some easy-to-use functions to extract and visualize the output of multivariate data analyses, including 'PCA' (Principal Component Analysis), 'CA' (Correspondence Analysis), 'MCA' (Multiple Correspondence Analysis), 'FAMD' (Factor Analysis of Mixed Data), 'MFA' (Multiple Factor Analysis) and 'HMFA' (Hierarchical Multiple Factor Analysis) functions from different R packages. It contains also functions for simplifying some clustering analysis steps and provides 'ggplot2' - based elegant data visualization.
Maintained by Alboukadel Kassambara. Last updated 5 years ago.
10.1 match 363 stars 14.13 score 15k scripts 52 dependents
r-forge
Rmpfr:Interface R to MPFR - Multiple Precision Floating-Point Reliable
Arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental ("special") functions. To this end, the package interfaces to the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library which itself is based on the 'GMP' (GNU Multiple Precision) Library.
Maintained by Martin Maechler. Last updated 4 months ago.
12.4 match 11.30 score 316 scripts 141 dependentsbioc
iSEE:Interactive SummarizedExperiment Explorer
Create an interactive Shiny-based graphical user interface for exploring data stored in SummarizedExperiment objects, including row- and column-level metadata. The interface supports transmission of selections between plots and tables, code tracking, interactive tours, interactive or programmatic initialization, preservation of app state, and extensibility to new panel types via S4 classes. Special attention is given to single-cell data in a SingleCellExperiment object with visualization of dimensionality reduction results.
Maintained by Kevin Rue-Albrecht. Last updated 12 days ago.
cellbasedassaysclusteringdimensionreductionfeatureextractiongeneexpressionguiimmunooncologyshinyappssinglecelltranscriptiontranscriptomicsvisualizationdimension-reductionfeature-extractiongene-expressionhacktoberfesthuman-cell-atlasshinysingle-cell
10.8 match 225 stars 12.86 score 380 scripts 9 dependents
n8thangreen
BCEA:Bayesian Cost Effectiveness Analysis
Produces an economic evaluation of a sample of suitable variables of cost and effectiveness / utility for two or more interventions, e.g. from a Bayesian model in the form of MCMC simulations. This package computes the most cost-effective alternative and produces graphical summaries and probabilistic sensitivity analysis, see Baio et al (2017) <doi:10.1007/978-3-319-55718-2>.
Maintained by Gianluca Baio. Last updated 2 months ago.
14.1 match 3 stars 9.90 score 243 scripts 3 dependents
smartdata-analysis-and-statistics
SimTOST:Sample Size Estimation for Bio-Equivalence Trials Through Simulation
Sample size estimation for bio-equivalence trials is supported through a simulation-based approach that extends the Two One-Sided Tests (TOST) procedure. The methodology provides flexibility in hypothesis testing, accommodates multiple treatment comparisons, and accounts for correlated endpoints. Users can model complex trial scenarios, including parallel and crossover designs, intra-subject variability, and different equivalence margins. Monte Carlo simulations enable accurate estimation of power and type I error rates, ensuring well-calibrated study designs. The statistical framework builds on established methods for equivalence testing and multiple hypothesis testing in bio-equivalence studies, as described in Schuirmann (1987) <doi:10.1007/BF01068419>, Mielke et al. (2018) <doi:10.1080/19466315.2017.1371071>, Shieh (2022) <doi:10.1371/journal.pone.0269128>, and Sozu et al. (2015) <doi:10.1007/978-3-319-22005-5>. Comprehensive documentation and vignettes guide users through implementation and interpretation of results.
Maintained by Thomas Debray. Last updated 27 days ago.
mcmcmulti-armmultiple-comparisonssample-size-calculationsample-size-estimationtrial-simulationopenblascpp
21.1 match 2 stars 6.47 score 7 scriptsbioc
EBSeq:An R package for gene and isoform differential expression analysis of RNA-seq data
Differential Expression analysis at both gene and isoform level using RNA-seq data
Maintained by Xiuyu Ma. Last updated 2 months ago.
immunooncologystatisticalmethoddifferentialexpressionmultiplecomparisonrnaseqsequencingcpp
17.2 match 7.77 score 162 scripts 6 dependents
kwstat
agridat:Agricultural Datasets
Datasets from books, papers, and websites related to agriculture. Example graphics and analyses are included. Data come from small-plot trials, multi-environment trials, uniformity trials, yield monitors, and more.
Maintained by Kevin Wright. Last updated 29 days ago.
12.0 match 125 stars 11.02 score 1.7k scripts 2 dependents
joshwlambert
DAISIEprep:Extracts Phylogenetic Island Community Data from Phylogenetic Trees
Extracts colonisation and branching times of island species to be used for analysis in the R package 'DAISIE'. It uses phylogenetic and endemicity data to extract the separate island colonists and store them.
Maintained by Joshua W. Lambert. Last updated 1 months ago.
data-scienceisland-biogeographyphylogenetics
19.0 match 6 stars 6.78 score 24 scripts
gateslab
gimme:Group Iterative Multiple Model Estimation
Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.
Maintained by Kathleen M Gates. Last updated 6 months ago.
16.7 match 26 stars 7.71 score 53 scripts
dmphillippo
multinma:Bayesian Network Meta-Analysis of Individual and Aggregate Data
Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Maintained by David M. Phillippo. Last updated 4 days ago.
14.1 match 35 stars 9.11 score 163 scripts
teppeiyamamoto
mediation:Causal Mediation Analysis
We implement parametric and non parametric mediation analysis. This package performs the methods and suggestions in Imai, Keele and Yamamoto (2010) <DOI:10.1214/10-STS321>, Imai, Keele and Tingley (2010) <DOI:10.1037/a0020761>, Imai, Tingley and Yamamoto (2013) <DOI:10.1111/j.1467-985X.2012.01032.x>, Imai and Yamamoto (2013) <DOI:10.1093/pan/mps040> and Yamamoto (2013) <http://web.mit.edu/teppei/www/research/IVmediate.pdf>. In addition to the estimation of causal mediation effects, the software also allows researchers to conduct sensitivity analysis for certain parametric models.
Maintained by Teppei Yamamoto. Last updated 6 years ago.
12.0 match 10.48 score 896 scripts 11 dependentsropensci
biomartr:Genomic Data Retrieval
Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized way to automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and metagenome retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL', and 'UniProt' databases. Furthermore, an interface to the 'BioMart' database (Smedley et al. (2009) <doi:10.1186/1471-2164-10-22>) allows users to retrieve functional annotation for genomic loci. In addition, users can download entire databases such as 'NCBI RefSeq' (Pruitt et al. (2007) <doi:10.1093/nar/gkl842>), 'NCBI nr', 'NCBI nt', 'NCBI Genbank' (Benson et al. (2013) <doi:10.1093/nar/gks1195>), etc. with only one command.
Maintained by Hajk-Georg Drost. Last updated 1 months ago.
biomartgenomic-data-retrievalannotation-retrievaldatabase-retrievalncbiensemblbiological-data-retrievalensembl-serversgenomegenome-annotationgenome-retrievalgenomicsmeta-analysismetagenomicsncbi-genbankpeer-reviewedproteomesequenced-genomes
11.0 match 218 stars 11.35 score 129 scripts 3 dependentsr-lib
slider:Sliding Window Functions
Provides type-stable rolling window functions over any R data type. Cumulative and expanding windows are also supported. For more advanced usage, an index can be used as a secondary vector that defines how sliding windows are to be created.
Maintained by Davis Vaughan. Last updated 1 months ago.
8.8 match 302 stars 13.92 score 848 scripts 99 dependentsbioc
variancePartition:Quantify and interpret drivers of variation in multilevel gene expression experiments
Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.
Maintained by Gabriel E. Hoffman. Last updated 2 months ago.
rnaseqgeneexpressiongenesetenrichmentdifferentialexpressionbatcheffectqualitycontrolregressionepigeneticsfunctionalgenomicstranscriptomicsnormalizationpreprocessingmicroarrayimmunooncologysoftware
10.4 match 7 stars 11.69 score 1.1k scripts 3 dependents
chaoliu-cl
conversim:Conversation Similarity Analysis Package
A comprehensive toolkit for analyzing and comparing conversations. This package provides functions to calculate various similarity measures between conversations, including topic, lexical, semantic, structural, stylistic, sentiment, participant, and timing similarities. It supports both pairwise conversation comparisons and analysis of multiple dyads.
Maintained by Chao Liu. Last updated 6 months ago.
28.3 match 4.30 score 10 scripts
merck
gMCPLite:Lightweight Graph Based Multiple Comparison Procedures
A lightweight fork of 'gMCP' with functions for graphical described multiple test procedures introduced in Bretz et al. (2009) <doi:10.1002/sim.3495> and Bretz et al. (2011) <doi:10.1002/bimj.201000239>. Implements a flexible function using 'ggplot2' to create multiplicity graph visualizations. Contains instructions of multiplicity graph and graphical testing for group sequential design, described in Maurer and Bretz (2013) <doi:10.1080/19466315.2013.807748>, with necessary unit testing using 'testthat'.
Maintained by Nan Xiao. Last updated 1 years ago.
20.2 match 11 stars 5.79 score 14 scripts
ohdsi
PatientLevelPrediction:Develop Clinical Prediction Models Using the Common Data Model
A user friendly way to create patient level prediction models using the Observational Medical Outcomes Partnership Common Data Model. Given a cohort of interest and an outcome of interest, the package can use data in the Common Data Model to build a large set of features. These features can then be used to fit a predictive model with a number of machine learning algorithms. This is further described in Reps (2017) <doi:10.1093/jamia/ocy032>.
Maintained by Egill Fridgeirsson. Last updated 10 days ago.
10.6 match 190 stars 10.85 score 297 scriptstslumley
mitools:Tools for Multiple Imputation of Missing Data
Tools to perform analyses and combine results from multiple-imputation datasets.
Maintained by Thomas Lumley. Last updated 6 years ago.
11.9 match 1 stars 9.50 score 716 scripts 249 dependents
stochastictree
stochtree:Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference
Flexible stochastic tree ensemble software. Robust implementations of Bayesian Additive Regression Trees (BART) Chipman, George, McCulloch (2010) <doi:10.1214/09-AOAS285> for supervised learning and Bayesian Causal Forests (BCF) Hahn, Murray, Carvalho (2020) <doi:10.1214/19-BA1195> for causal inference. Enables model serialization and parallel sampling and provides a low-level interface for custom stochastic forest samplers.
Maintained by Drew Herren. Last updated 22 hours ago.
bartbayesian-machine-learningbayesian-methodsdecision-treesgradient-boosted-treesmachine-learningprobabilistic-modelstree-ensemblescpp
13.2 match 22 stars 8.57 score 40 scripts
hughjonesd
huxtable:Easily Create and Style Tables for LaTeX, HTML and Other Formats
Creates styled tables for data presentation. Export to HTML, LaTeX, RTF, 'Word', 'Excel', and 'PowerPoint'. Simple, modern interface to manipulate borders, size, position, captions, colours, text styles and number formatting. Table cells can span multiple rows and/or columns. Includes a 'huxreg' function for creation of regression tables, and 'quick_*' one-liners to print data to a new document.
Maintained by David Hugh-Jones. Last updated 13 days ago.
htmlhuxtablelatexmicrosoft-wordpowerpointreproducible-researchtables
7.9 match 323 stars 13.93 score 1.9k scripts 16 dependents
npm27
lrd:A Package for Processing Lexical Response Data
Lexical response data is a package that can be used for processing cued-recall, free-recall, and sentence responses from memory experiments.
Maintained by Nicholas Maxwell. Last updated 3 years ago.
20.7 match 3 stars 5.30 score 33 scripts
thibautjombart
apex:Phylogenetic Methods for Multiple Gene Data
Toolkit for the analysis of multiple gene data (Jombart et al. 2017) <doi:10.1111/1755-0998.12567>. 'apex' implements the new S4 classes 'multidna', 'multiphyDat' and associated methods to handle aligned DNA sequences from multiple genes.
Maintained by Klaus Schliep. Last updated 1 years ago.
17.0 match 5 stars 6.40 score 54 scripts
elliecurnow
midoc:A Decision-Making System for Multiple Imputation
A guidance system for analysis with missing data. It incorporates expert, up-to-date methodology to help researchers choose the most appropriate analysis approach when some data are missing. You provide the available data and the assumed causal structure, including the likely causes of missing data. 'midoc' will advise which analysis approaches can be used, and how best to perform them. 'midoc' follows the framework for the treatment and reporting of missing data in observational studies (TARMOS). Lee et al (2021). <doi:10.1016/j.jclinepi.2021.01.008>.
Maintained by Elinor Curnow. Last updated 6 months ago.
missing-datamultiple-imputation
20.5 match 6 stars 5.32 score 8 scripts
rmheiberger
HH:Statistical Analysis and Data Display: Heiberger and Holland
Support software for Statistical Analysis and Data Display (Second Edition, Springer, ISBN 978-1-4939-2121-8, 2015) and (First Edition, Springer, ISBN 0-387-40270-5, 2004) by Richard M. Heiberger and Burt Holland. This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The second edition includes redesigned graphics and additional chapters. The authors emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. All functions introduced in the book are in the package. R code for all examples, both graphs and tables, in the book is included in the scripts directory of the package.
Maintained by Richard M. Heiberger. Last updated 1 months ago.
16.9 match 3 stars 6.42 score 752 scripts 5 dependents
cardiomoon
ggiraphExtra:Make Interactive 'ggplot2'. Extension to 'ggplot2' and 'ggiraph'
Collection of functions to enhance 'ggplot2' and 'ggiraph'. Provides functions for exploratory plots. All plot can be a 'static' plot or an 'interactive' plot using 'ggiraph'.
Maintained by Keon-Woong Moon. Last updated 4 years ago.
11.8 match 48 stars 8.93 score 402 scripts 3 dependentskornl
mutoss:Unified Multiple Testing Procedures
Designed to ease the application and comparison of multiple hypothesis testing procedures for FWER, gFWER, FDR and FDX. Methods are standardized and usable by the accompanying 'mutossGUI'.
Maintained by Kornelius Rohmeyer. Last updated 12 months ago.
12.4 match 4 stars 8.44 score 24 scripts 16 dependents
beckerbenj
eatGADS:Data Management of Large Hierarchical Data
Import 'SPSS' data, handle and change 'SPSS' meta data, store and access large hierarchical data in 'SQLite' data bases.
Maintained by Benjamin Becker. Last updated 24 days ago.
14.0 match 1 stars 7.36 score 34 scripts 1 dependents
mplex
multiplex:Algebraic Tools for the Analysis of Multiple Social Networks
Algebraic procedures for analyses of multiple social networks are delivered with this package as described in Ostoic (2020) <DOI:10.18637/jss.v092.i11>. 'multiplex' makes possible, among other things, to create and manipulate multiplex, multimode, and multilevel network data with different formats. Effective ways are available to treat multiple networks with routines that combine algebraic systems like the partially ordered semigroup with decomposition procedures or semiring structures with the relational bundles occurring in different types of multivariate networks. 'multiplex' provides also an algebraic approach for affiliation networks through Galois derivations between families of the pairs of subsets in the two domains of the network with visualization options.
Maintained by Antonio Rivero Ostoic. Last updated 2 months ago.
algebranetwork-analysissemigroupsemiring
12.7 match 23 stars 8.12 score 69 scripts 2 dependents
bcallaway11
did:Treatment Effects with Multiple Periods and Groups
The standard Difference-in-Differences (DID) setup involves two periods and two groups -- a treated group and untreated group. Many applications of DID methods involve more than two periods and have individuals that are treated at different points in time. This package contains tools for computing average treatment effect parameters in Difference in Differences setups with more than two periods and with variation in treatment timing using the methods developed in Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>. The main parameters are group-time average treatment effects which are the average treatment effect for a particular group at a a particular time. These can be aggregated into a fewer number of treatment effect parameters, and the package deals with the cases where there is selective treatment timing, dynamic treatment effects, calendar time effects, or combinations of these. There are also functions for testing the Difference in Differences assumption, and plotting group-time average treatment effects.
Maintained by Brantly Callaway. Last updated 4 months ago.
8.5 match 327 stars 12.01 score 696 scripts 3 dependents
simongrund1
mitml:Tools for Multiple Imputation in Multilevel Modeling
Provides tools for multiple imputation of missing data in multilevel modeling. Includes a user-friendly interface to the packages 'pan' and 'jomo', and several functions for visualization, data management and the analysis of multiply imputed data sets.
Maintained by Simon Grund. Last updated 1 years ago.
imputationmissing-datamixed-effectsmultilevel-datamultilevel-models
8.3 match 29 stars 12.36 score 246 scripts 153 dependents
cvxgrp
CVXR:Disciplined Convex Optimization
An object-oriented modeling language for disciplined convex programming (DCP) as described in Fu, Narasimhan, and Boyd (2020, <doi:10.18637/jss.v094.i14>). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution. Interfaces to solvers on CRAN and elsewhere are provided, both commercial and open source.
Maintained by Anqi Fu. Last updated 4 months ago.
7.9 match 207 stars 12.89 score 768 scripts 51 dependents
wilkelab
cowplot:Streamlined Plot Theme and Plot Annotations for 'ggplot2'
Provides various features that help with creating publication-quality figures with 'ggplot2', such as a set of themes, functions to align plots and arrange them into complex compound figures, and functions that make it easy to annotate plots and or mix plots with images. The package was originally written for internal use in the Wilke lab, hence the name (Claus O. Wilke's plot package). It has also been used extensively in the book Fundamentals of Data Visualization.
Maintained by Claus O. Wilke. Last updated 2 months ago.
5.4 match 714 stars 18.83 score 75k scripts 1.4k dependents
jimmcl
trajr:Animal Trajectory Analysis
A toolbox to assist with statistical analysis of animal trajectories. It provides simple access to algorithms for calculating and assessing a variety of characteristics such as speed and acceleration, as well as multiple measures of straightness or tortuosity. Some support is provided for 3-dimensional trajectories. McLean & Skowron Volponi (2018) <doi:10.1111/eth.12739>.
Maintained by Jim McLean. Last updated 8 months ago.
13.3 match 27 stars 7.69 score 151 scripts
config-i1
smooth:Forecasting Using State Space Models
Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. The package includes ADAM (Svetunkov, 2023, <https://openforecast.org/adam/>), Exponential Smoothing (Hyndman et al., 2008, <doi: 10.1007/978-3-540-71918-2>), SARIMA (Svetunkov & Boylan, 2019 <doi: 10.1080/00207543.2019.1600764>), Complex Exponential Smoothing (Svetunkov & Kourentzes, 2018, <doi: 10.13140/RG.2.2.24986.29123>), Simple Moving Average (Svetunkov & Petropoulos, 2018 <doi: 10.1080/00207543.2017.1380326>) and several simulation functions. It also allows dealing with intermittent demand based on the iETS framework (Svetunkov & Boylan, 2019, <doi: 10.13140/RG.2.2.35897.06242>).
Maintained by Ivan Svetunkov. Last updated 13 hours ago.
arimaarima-forecastingcesetsexponential-smoothingforecaststate-spacetime-seriesopenblascpp
7.3 match 90 stars 13.83 score 412 scripts 25 dependents
tidymodels
recipes:Preprocessing and Feature Engineering Steps for Modeling
A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.
Maintained by Max Kuhn. Last updated 7 days ago.
5.4 match 584 stars 18.71 score 7.2k scripts 380 dependents
winvector
wrapr:Wrap R Tools for Debugging and Parametric Programming
Tools for writing and debugging R code. Provides: '%.>%' dot-pipe (an 'S3' configurable pipe), unpack/to (R style multiple assignment/return), 'build_frame()'/'draw_frame()' ('data.frame' example tools), 'qc()' (quoting concatenate), ':=' (named map builder), 'let()' (converts non-standard evaluation interfaces to parametric standard evaluation interfaces, inspired by 'gtools::strmacro()' and 'base::bquote()'), and more.
Maintained by John Mount. Last updated 2 years ago.
8.9 match 137 stars 11.11 score 390 scripts 12 dependents
robinhankin
MM:The Multiplicative Multinomial Distribution
Various utilities for the Multiplicative Multinomial distribution.
Maintained by Robin K. S. Hankin. Last updated 10 months ago.
21.2 match 4.64 score 22 scriptsbioc
EWCE:Expression Weighted Celltype Enrichment
Used to determine which cell types are enriched within gene lists. The package provides tools for testing enrichments within simple gene lists (such as human disease associated genes) and those resulting from differential expression studies. The package does not depend upon any particular Single Cell Transcriptome dataset and user defined datasets can be loaded in and used in the analyses.
Maintained by Alan Murphy. Last updated 1 months ago.
geneexpressiontranscriptiondifferentialexpressiongenesetenrichmentgeneticsmicroarraymrnamicroarrayonechannelrnaseqbiomedicalinformaticsproteomicsvisualizationfunctionalgenomicssinglecelldeconvolutionsingle-cellsingle-cell-rna-seqtranscriptomics
10.6 match 56 stars 9.29 score 99 scripts
insightsengineering
rtables:Reporting Tables
Reporting tables often have structure that goes beyond simple rectangular data. The 'rtables' package provides a framework for declaring complex multi-level tabulations and then applying them to data. This framework models both tabulation and the resulting tables as hierarchical, tree-like objects which support sibling sub-tables, arbitrary splitting or grouping of data in row and column dimensions, cells containing multiple values, and the concept of contextual summary computations. A convenient pipe-able interface is provided for declaring table layouts and the corresponding computations, and then applying them to data.
Maintained by Joe Zhu. Last updated 2 months ago.
7.2 match 232 stars 13.65 score 238 scripts 17 dependents
psychmeta
psychmeta:Psychometric Meta-Analysis Toolkit
Tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more. Bugs can be reported to <https://github.com/psychmeta/psychmeta/issues> or <issues@psychmeta.com>.
Maintained by Jeffrey A. Dahlke. Last updated 9 months ago.
hacktoberfestmeta-analysispsychologypsychometricpsychometrics
11.8 match 57 stars 8.25 score 151 scripts
fishr-core-team
FSAdata:Data to Support Fish Stock Assessment ('FSA') Package
The datasets to support the Fish Stock Assessment ('FSA') package.
Maintained by Derek Ogle. Last updated 2 years ago.
fishfisheriesfisheries-stock-assessmentfishr-websitestock-assessment
17.0 match 13 stars 5.67 score 285 scripts
sistm
NPflow:Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry Data
Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions modeling oriented towards flow-cytometry data preprocessing applications. Method is detailed in: Hejblum, Alkhassimn, Gottardo, Caron & Thiebaut (2019) <doi: 10.1214/18-AOAS1209>.
Maintained by Boris P Hejblum. Last updated 1 years ago.
21.6 match 4 stars 4.45 score 47 scripts 1 dependentsropensci
phylotaR:Automated Phylogenetic Sequence Cluster Identification from 'GenBank'
A pipeline for the identification, within taxonomic groups, of orthologous sequence clusters from 'GenBank' <https://www.ncbi.nlm.nih.gov/genbank/> as the first step in a phylogenetic analysis. The pipeline depends on a local alignment search tool and is, therefore, not dependent on differences in gene naming conventions and naming errors.
Maintained by Shixiang Wang. Last updated 8 months ago.
blastngenbankpeer-reviewedphylogeneticssequence-alignment
16.3 match 23 stars 5.86 score 156 scripts
nredell
forecastML:Time Series Forecasting with Machine Learning Methods
The purpose of 'forecastML' is to simplify the process of multi-step-ahead forecasting with standard machine learning algorithms. 'forecastML' supports lagged, dynamic, static, and grouping features for modeling single and grouped numeric or factor/sequence time series. In addition, simple wrapper functions are used to support model-building with most R packages. This approach to forecasting is inspired by Bergmeir, Hyndman, and Koo's (2018) paper "A note on the validity of cross-validation for evaluating autoregressive time series prediction" <doi:10.1016/j.csda.2017.11.003>.
Maintained by Nickalus Redell. Last updated 5 years ago.
deep-learningdirect-forecastingforecastforecastingmachine-learningmulti-step-ahead-forecastingneural-networkpythontime-series
12.3 match 131 stars 7.64 score 134 scriptsfishr-core-team
FSA:Simple Fisheries Stock Assessment Methods
A variety of simple fish stock assessment methods.
Maintained by Derek H. Ogle. Last updated 2 months ago.
fishfisheriesfisheries-managementfisheries-stock-assessmentpopulation-dynamicsstock-assessment
8.4 match 68 stars 11.08 score 1.7k scripts 6 dependentskassambara
ggpubr:'ggplot2' Based Publication Ready Plots
The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.
Maintained by Alboukadel Kassambara. Last updated 2 years ago.
5.6 match 1.2k stars 16.68 score 65k scripts 409 dependentsinsightsengineering
tern:Create Common TLGs Used in Clinical Trials
Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.
Maintained by Joe Zhu. Last updated 2 months ago.
clinical-trialsgraphslistingsnestoutputstables
7.3 match 79 stars 12.62 score 186 scripts 9 dependents
uupharmacometrics
xpose4:Diagnostics for Nonlinear Mixed-Effect Models
A model building aid for nonlinear mixed-effects (population) model analysis using NONMEM, facilitating data set checkout, exploration and visualization, model diagnostics, candidate covariate identification and model comparison. The methods are described in Keizer et al. (2013) <doi:10.1038/psp.2013.24>, and Jonsson et al. (1999) <doi:10.1016/s0169-2607(98)00067-4>.
Maintained by Andrew C. Hooker. Last updated 1 years ago.
diagnosticsnonmempharmacometricspopulation-modelxpose
12.7 match 35 stars 7.30 score 315 scripts
philchalmers
SimDesign:Structure for Organizing Monte Carlo Simulation Designs
Provides tools to safely and efficiently organize and execute Monte Carlo simulation experiments in R. The package controls the structure and back-end of Monte Carlo simulation experiments by utilizing a generate-analyse-summarise workflow. The workflow safeguards against common simulation coding issues, such as automatically re-simulating non-convergent results, prevents inadvertently overwriting simulation files, catches error and warning messages during execution, implicitly supports parallel processing with high-quality random number generation, and provides tools for managing high-performance computing (HPC) array jobs submitted to schedulers such as SLURM. For a pedagogical introduction to the package see Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>. For a more in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.
Maintained by Phil Chalmers. Last updated 11 hours ago.
monte-carlo-simulationsimulationsimulation-framework
6.9 match 62 stars 13.38 score 253 scripts 46 dependentsphilchalmers
mirt:Multidimensional Item Response Theory
Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.
Maintained by Phil Chalmers. Last updated 12 days ago.
6.1 match 210 stars 14.98 score 2.5k scripts 40 dependents
thomasp85
ggraph:An Implementation of Grammar of Graphics for Graphs and Networks
The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. ggraph is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.
Maintained by Thomas Lin Pedersen. Last updated 1 years ago.
ggplot-extensionggplot2graph-visualizationnetwork-visualizationvisualizationcpp
5.2 match 1.1k stars 16.96 score 9.2k scripts 111 dependents
martin3141
spant:MR Spectroscopy Analysis Tools
Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.
Maintained by Martin Wilson. Last updated 1 months ago.
brainmrimrsmrshubspectroscopyfortran
10.2 match 25 stars 8.52 score 81 scriptscran
wavethresh:Wavelets Statistics and Transforms
Performs 1, 2 and 3D real and complex-valued wavelet transforms, nondecimated transforms, wavelet packet transforms, nondecimated wavelet packet transforms, multiple wavelet transforms, complex-valued wavelet transforms, wavelet shrinkage for various kinds of data, locally stationary wavelet time series, nonstationary multiscale transfer function modeling, density estimation.
Maintained by Guy Nason. Last updated 7 months ago.
14.7 match 5.89 score 41 dependents
natverse
nat:NeuroAnatomy Toolbox for Analysis of 3D Image Data
NeuroAnatomy Toolbox (nat) enables analysis and visualisation of 3D biological image data, especially traced neurons. Reads and writes 3D images in NRRD and 'Amira' AmiraMesh formats and reads surfaces in 'Amira' hxsurf format. Traced neurons can be imported from and written to SWC and 'Amira' LineSet and SkeletonGraph formats. These data can then be visualised in 3D via 'rgl', manipulated including applying calculated registrations, e.g. using the 'CMTK' registration suite, and analysed. There is also a simple representation for neurons that have been subjected to 3D skeletonisation but not formally traced; this allows morphological comparison between neurons including searches and clustering (via the 'nat.nblast' extension package).
Maintained by Gregory Jefferis. Last updated 5 months ago.
3dconnectomicsimage-analysisneuroanatomyneuroanatomy-toolboxneuronneuron-morphologyneurosciencevisualisation
8.7 match 67 stars 9.94 score 436 scripts 2 dependents
mrcieu
TwoSampleMR:Two Sample MR Functions and Interface to MRC Integrative Epidemiology Unit OpenGWAS Database
A package for performing Mendelian randomization using GWAS summary data. It uses the IEU OpenGWAS database <https://gwas.mrcieu.ac.uk/> to automatically obtain data, and a wide range of methods to run the analysis.
Maintained by Gibran Hemani. Last updated 12 days ago.
7.6 match 467 stars 11.23 score 1.7k scripts 1 dependentsr-forge
multcomp:Simultaneous Inference in General Parametric Models
Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).
Maintained by Torsten Hothorn. Last updated 2 months ago.
6.3 match 13.49 score 7.5k scripts 366 dependents
sfcheung
manymome:Mediation, Moderation and Moderated-Mediation After Model Fitting
Computes indirect effects, conditional effects, and conditional indirect effects in a structural equation model or path model after model fitting, with no need to define any user parameters or label any paths in the model syntax, using the approach presented in Cheung and Cheung (2024) <doi:10.3758/s13428-023-02224-z>. Can also form bootstrap confidence intervals by doing bootstrapping only once and reusing the bootstrap estimates in all subsequent computations. Supports bootstrap confidence intervals for standardized (partially or completely) indirect effects, conditional effects, and conditional indirect effects as described in Cheung (2009) <doi:10.3758/BRM.41.2.425> and Cheung, Cheung, Lau, Hui, and Vong (2022) <doi:10.1037/hea0001188>. Model fitting can be done by structural equation modeling using lavaan() or regression using lm().
Maintained by Shu Fai Cheung. Last updated 24 days ago.
bootstrappingconfidence-intervallavaanmanymomemediationmoderated-mediationmoderationregressionsemstandardized-effect-sizestructural-equation-modeling
10.5 match 1 stars 8.06 score 172 scripts 4 dependents
braverock
PortfolioAnalytics:Portfolio Analysis, Including Numerical Methods for Optimization of Portfolios
Portfolio optimization and analysis routines and graphics.
Maintained by Brian G. Peterson. Last updated 3 months ago.
7.4 match 81 stars 11.49 score 626 scripts 2 dependents
baptiste
egg:Extensions for 'ggplot2': Custom Geom, Custom Themes, Plot Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel Size
Miscellaneous functions to help customise 'ggplot2' objects. High-level functions are provided to post-process 'ggplot2' layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. Other functions include a custom 'geom', and helper functions to enforce symmetric scales or add tags to facetted plots.
Maintained by Baptiste Auguie. Last updated 4 years ago.
7.1 match 13 stars 11.84 score 2.4k scripts 67 dependentskassambara
rstatix:Pipe-Friendly Framework for Basic Statistical Tests
Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and 'Cramer V' for the association between categorical variables. The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances.
Maintained by Alboukadel Kassambara. Last updated 2 years ago.
5.5 match 456 stars 15.16 score 11k scripts 420 dependents
eitsupi
neopolars:R Bindings for the 'polars' Rust Library
Lightning-fast 'DataFrame' library written in 'Rust'. Convert R data to 'Polars' data and vice versa. Perform fast, lazy, larger-than-memory and optimized data queries. 'Polars' is interoperable with the package 'arrow', as both are based on the 'Apache Arrow' Columnar Format.
Maintained by Tatsuya Shima. Last updated 2 days ago.
17.2 match 40 stars 4.86 score 1 scripts
statnet
ergm.multi:Fit, Simulate and Diagnose Exponential-Family Models for Multiple or Multilayer Networks
A set of extensions for the 'ergm' package to fit multilayer/multiplex/multirelational networks and samples of multiple networks. 'ergm.multi' is a part of the Statnet suite of packages for network analysis. See Krivitsky, Koehly, and Marcum (2020) <doi:10.1007/s11336-020-09720-7> and Krivitsky, Coletti, and Hens (2023) <doi:10.1080/01621459.2023.2242627>.
Maintained by Pavel N. Krivitsky. Last updated 4 months ago.
8.6 match 14 stars 9.67 score 11 scripts 5 dependents
iiasa
ibis.iSDM:Modelling framework for integrated biodiversity distribution scenarios
Integrated framework of modelling the distribution of species and ecosystems in a suitability framing. This package allows the estimation of integrated species distribution models (iSDM) based on several sources of evidence and provided presence-only and presence-absence datasets. It makes heavy use of point-process models for estimating habitat suitability and allows to include spatial latent effects and priors in the estimation. To do so 'ibis.iSDM' supports a number of engines for Bayesian and more non-parametric machine learning estimation. Further, the 'ibis.iSDM' is specifically customized to support spatial-temporal projections of habitat suitability into the future.
Maintained by Martin Jung. Last updated 4 months ago.
bayesianbiodiversityintegrated-frameworkpoisson-processscenariossdmspatial-grainspatial-predictionsspecies-distribution-modelling
19.0 match 21 stars 4.36 score 12 scripts 1 dependentsbioc
Maaslin2:"Multivariable Association Discovery in Population-scale Meta-omics Studies"
MaAsLin2 is comprehensive R package for efficiently determining multivariable association between clinical metadata and microbial meta'omic features. MaAsLin2 relies on general linear models to accommodate most modern epidemiological study designs, including cross-sectional and longitudinal, and offers a variety of data exploration, normalization, and transformation methods. MaAsLin2 is the next generation of MaAsLin.
Maintained by Lauren McIver. Last updated 5 months ago.
metagenomicssoftwaremicrobiomenormalizationbiobakerybioconductordifferential-abundance-analysisfalse-discovery-ratemultiple-covariatespublicrepeated-measurestools
7.5 match 133 stars 11.03 score 532 scripts 3 dependentsbraverock
PerformanceAnalytics:Econometric Tools for Performance and Risk Analysis
Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.
Maintained by Brian G. Peterson. Last updated 3 months ago.
5.2 match 222 stars 15.93 score 4.8k scripts 20 dependentsinsightsengineering
rbmi:Reference Based Multiple Imputation
Implements standard and reference based multiple imputation methods for continuous longitudinal endpoints (Gower-Page et al. (2022) <doi:10.21105/joss.04251>). In particular, this package supports deterministic conditional mean imputation and jackknifing as described in Wolbers et al. (2022) <doi:10.1002/pst.2234>, Bayesian multiple imputation as described in Carpenter et al. (2013) <doi:10.1080/10543406.2013.834911>, and bootstrapped maximum likelihood imputation as described in von Hippel and Bartlett (2021) <doi: 10.1214/20-STS793>.
Maintained by Isaac Gravestock. Last updated 25 days ago.
9.3 match 18 stars 8.78 score 33 scripts 1 dependentsbioc
sitePath:Phylogeny-based sequence clustering with site polymorphism
Using site polymorphism is one of the ways to cluster DNA/protein sequences but it is possible for the sequences with the same polymorphism on a single site to be genetically distant. This package is aimed at clustering sequences using site polymorphism and their corresponding phylogenetic trees. By considering their location on the tree, only the structurally adjacent sequences will be clustered. However, the adjacent sequences may not necessarily have the same polymorphism. So a branch-and-bound like algorithm is used to minimize the entropy representing the purity of site polymorphism of each cluster.
Maintained by Chengyang Ji. Last updated 5 months ago.
alignmentmultiplesequencealignmentphylogeneticssnpsoftwaremutationcpp
15.7 match 8 stars 5.20 score 9 scripts
bips-hb
micd:Multiple Imputation in Causal Graph Discovery
Modified functions of the package 'pcalg' and some additional functions to run the PC and the FCI (Fast Causal Inference) algorithm for constraint-based causal discovery in incomplete and multiply imputed datasets. Foraita R, Friemel J, Gรผnther K, Behrens T, Bullerdiek J, Nimzyk R, Ahrens W, Didelez V (2020) <doi:10.1111/rssa.12565>; Andrews RM, Foraita R, Didelez V, Witte J (2021) <arXiv:2108.13395>; Witte J, Foraita R, Didelez V (2022) <doi:10.1002/sim.9535>.
Maintained by Ronja Foraita. Last updated 2 years ago.
causal-discoverygraphical-modelsmultiple-imputation
22.0 match 5 stars 3.70 score 20 scripts
novartis
xgxr:Exploratory Graphics for Pharmacometrics
Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx/>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
Maintained by Andrew Stein. Last updated 1 years ago.
10.5 match 13 stars 7.76 score 105 scripts 5 dependentsbioc
motifStack:Plot stacked logos for single or multiple DNA, RNA and amino acid sequence
The motifStack package is designed for graphic representation of multiple motifs with different similarity scores. It works with both DNA/RNA sequence motif and amino acid sequence motif. In addition, it provides the flexibility for users to customize the graphic parameters such as the font type and symbol colors.
Maintained by Jianhong Ou. Last updated 2 months ago.
sequencematchingvisualizationsequencingmicroarrayalignmentchipchipchipseqmotifannotationdataimport
10.2 match 7.93 score 188 scripts 6 dependents
mariechion
mi4p:Multiple Imputation for Proteomics
A framework for multiple imputation for proteomics is proposed by Marie Chion, Christine Carapito and Frederic Bertrand (2021) <doi:10.1371/journal.pcbi.1010420>. It is dedicated to dealing with multiple imputation for proteomics.
Maintained by Frederic Bertrand. Last updated 6 months ago.
16.2 match 6 stars 4.91 score 27 scriptsropensci
paleobioDB:Download and Process Data from the Paleobiology Database
Includes functions to wrap most endpoints of the 'PaleobioDB' API and functions to visualize and process the fossil data. The API documentation for the Paleobiology Database can be found at <https://paleobiodb.org/data1.2/>.
Maintained by Adriรกn Castro Insua. Last updated 1 years ago.
12.8 match 42 stars 6.19 score 74 scripts
amalan-constat
fitODBOD:Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD
Contains Probability Mass Functions, Cumulative Mass Functions, Negative Log Likelihood value, parameter estimation and modeling data using Binomial Mixture Distributions (BMD) (Manoj et al (2013) <doi:10.5539/ijsp.v2n2p24>) and Alternate Binomial Distributions (ABD) (Paul (1985) <doi:10.1080/03610928508828990>), also Journal article to use the package(<doi:10.21105/joss.01505>).
Maintained by Amalan Mahendran. Last updated 4 months ago.
binomial-outcome-dataoverdispersion
17.8 match 1 stars 4.44 score 139 scripts
japal
zCompositions:Treatment of Zeros, Left-Censored and Missing Values in Compositional Data Sets
Principled methods for the imputation of zeros, left-censored and missing data in compositional data sets (Palarea-Albaladejo and Martin-Fernandez (2015) <doi:10.1016/j.chemolab.2015.02.019>).
Maintained by Javier Palarea-Albaladejo. Last updated 9 months ago.
censored-datacompositional-dataimputation-methodsmissing-datanondetection
9.4 match 7 stars 8.40 score 370 scripts 11 dependents
prioritizr
prioritizr:Systematic Conservation Prioritization in R
Systematic conservation prioritization using mixed integer linear programming (MILP). It provides a flexible interface for building and solving conservation planning problems. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. By using exact algorithm solvers, solutions can be generated that are guaranteed to be optimal (or within a pre-specified optimality gap). Furthermore, conservation problems can be constructed to optimize the spatial allocation of different management actions or zones, meaning that conservation practitioners can identify solutions that benefit multiple stakeholders. To solve large-scale or complex conservation planning problems, users should install the Gurobi optimization software (available from <https://www.gurobi.com/>) and the 'gurobi' R package (see Gurobi Installation Guide vignette for details). Users can also install the IBM CPLEX software (<https://www.ibm.com/products/ilog-cplex-optimization-studio/cplex-optimizer>) and the 'cplexAPI' R package (available at <https://github.com/cran/cplexAPI>). Additionally, the 'rcbc' R package (available at <https://github.com/dirkschumacher/rcbc>) can be used to generate solutions using the CBC optimization software (<https://github.com/coin-or/Cbc>). For further details, see Hanson et al. (2025) <doi:10.1111/cobi.14376>.
Maintained by Richard Schuster. Last updated 12 days ago.
biodiversityconservationconservation-planneroptimizationprioritizationsolverspatialcpp
6.7 match 124 stars 11.82 score 584 scripts 2 dependents
andrewhooker
PopED:Population (and Individual) Optimal Experimental Design
Optimal experimental designs for both population and individual studies based on nonlinear mixed-effect models. Often this is based on a computation of the Fisher Information Matrix. This package was developed for pharmacometric problems, and examples and predefined models are available for these types of systems. The methods are described in Nyberg et al. (2012) <doi:10.1016/j.cmpb.2012.05.005>, and Foracchia et al. (2004) <doi:10.1016/S0169-2607(03)00073-7>.
Maintained by Andrew C. Hooker. Last updated 5 months ago.
nlmeoptimal-designpharmacodynamicspharmacokineticspharmacometricspkpdpopulationpopulation-model
8.2 match 33 stars 9.58 score 300 scripts 1 dependentspharmaverse
sdtmchecks:Data Quality Checks for Study Data Tabulation Model (SDTM) Datasets
A series of checks to identify common issues in Study Data Tabulation Model (SDTM) datasets. These checks are intended to be generalizable, actionable, and meaningful for analysis.
Maintained by Will Harris. Last updated 3 months ago.
10.2 match 21 stars 7.66 score 15 scripts
tidyverse
purrr:Functional Programming Tools
A complete and consistent functional programming toolkit for R.
Maintained by Hadley Wickham. Last updated 1 months ago.
3.5 match 1.3k stars 22.12 score 59k scripts 6.9k dependents
gergness
srvyr:'dplyr'-Like Syntax for Summary Statistics of Survey Data
Use piping, verbs like 'group_by' and 'summarize', and other 'dplyr' inspired syntactic style when calculating summary statistics on survey data using functions from the 'survey' package.
Maintained by Greg Freedman Ellis. Last updated 1 months ago.
5.6 match 215 stars 13.88 score 1.8k scripts 15 dependents
evalclass
precrec:Calculate Accurate Precision-Recall and ROC (Receiver Operator Characteristics) Curves
Accurate calculations and visualization of precision-recall and ROC (Receiver Operator Characteristics) curves. Saito and Rehmsmeier (2015) <doi:10.1371/journal.pone.0118432>.
Maintained by Takaya Saito. Last updated 1 years ago.
8.1 match 45 stars 9.59 score 496 scripts 5 dependentsadeverse
adegraphics:An S4 Lattice-Based Package for the Representation of Multivariate Data
Graphical functionalities for the representation of multivariate data. It is a complete re-implementation of the functions available in the 'ade4' package.
Maintained by Aurรฉlie Siberchicot. Last updated 8 months ago.
7.5 match 9 stars 10.37 score 386 scripts 6 dependents
nathaneastwood
poorman:A Poor Man's Dependency Free Recreation of 'dplyr'
A replication of key functionality from 'dplyr' and the wider 'tidyverse' using only 'base'.
Maintained by Nathan Eastwood. Last updated 1 years ago.
base-rdata-manipulationgrammar
7.1 match 341 stars 10.79 score 156 scripts 27 dependents
yufree
enviGCMS:GC/LC-MS Data Analysis for Environmental Science
Gas/Liquid Chromatography-Mass Spectrometer(GC/LC-MS) Data Analysis for Environmental Science. This package covered topics such molecular isotope ratio, matrix effects and Short-Chain Chlorinated Paraffins analysis etc. in environmental analysis.
Maintained by Miao YU. Last updated 2 months ago.
environmentmass-spectrometrymetabolomics
11.9 match 17 stars 6.49 score 30 scripts 1 dependents
r-econometrics
lfe:Linear Group Fixed Effects
Transforms away factors with many levels prior to doing an OLS. Useful for estimating linear models with multiple group fixed effects, and for estimating linear models which uses factors with many levels as pure control variables. See Gaure (2013) <doi:10.1016/j.csda.2013.03.024> Includes support for instrumental variables, conditional F statistics for weak instruments, robust and multi-way clustered standard errors, as well as limited mobility bias correction (Gaure 2014 <doi:10.1002/sta4.68>). Since version 3.0, it provides dedicated functions to estimate Poisson models.
Maintained by Mauricio Vargas Sepulveda. Last updated 1 years ago.
7.4 match 10.30 score 1.8k scripts 5 dependents
swarchal
platetools:Tools and Plots for Multi-Well Plates
Collection of functions for working with multi-well microtitre plates, mainly 96, 384 and 1536 well plates.
Maintained by Scott Warchal. Last updated 1 years ago.
12.3 match 54 stars 6.20 score 146 scripts
xsswang
remiod:Reference-Based Multiple Imputation for Ordinal/Binary Response
Reference-based multiple imputation of ordinal and binary responses under Bayesian framework, as described in Wang and Liu (2022) <arXiv:2203.02771>. Methods for missing-not-at-random include Jump-to-Reference (J2R), Copy Reference (CR), and Delta Adjustment which can generate tipping point analysis.
Maintained by Tony Wang. Last updated 2 years ago.
bayesiancontrol-basedcopy-referencedelta-adjustmentgeneralized-linear-modelsglmjagsjump-to-referencemcmcmissing-at-randommissing-datamissing-not-at-randommultiple-imputationnon-ignorableordinal-regressionpattern-mixture-modelreference-basedstatisticscpp
17.7 match 4.30 score 3 scriptsbioc
MultiAssayExperiment:Software for the integration of multi-omics experiments in Bioconductor
Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.
Maintained by Marcel Ramos. Last updated 2 months ago.
infrastructuredatarepresentationbioconductorbioconductor-packagegenomicsnci-itcrtcgau24ca289073
5.1 match 71 stars 14.95 score 670 scripts 127 dependents
netfacs
NetFACS:Network Applications to Facial Communication Data
Functions to analyze and visualize communication data, based on network theory and resampling methods. Farine, D. R. (2017) <doi:10.1111/2041-210X.12772>; Carsey, T., & Harden, J. (2014) <doi:10.4135/9781483319605>. Primarily targeted at datasets of facial expressions coded with the Facial Action Coding System. Ekman, P., Friesen, W. V., & Hager, J. C. (2002). "Facial action coding system - investigator's guide" <https://www.paulekman.com/facial-action-coding-system/>.
Maintained by Alan V. Rincon. Last updated 11 months ago.
14.9 match 8 stars 5.08 score 5 scriptsbioc
xcms:LC-MS and GC-MS Data Analysis
Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.
Maintained by Steffen Neumann. Last updated 3 days ago.
immunooncologymassspectrometrymetabolomicsbioconductorfeature-detectionmass-spectrometrypeak-detectioncpp
5.3 match 196 stars 14.31 score 984 scripts 11 dependents
samuel-marsh
scCustomize:Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing
Collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using 'R'. 'scCustomize' aims to provide 1) Customized visualizations for aid in ease of use and to create more aesthetic and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces of code in scRNA-seq analysis with a single or group of functions. For citation please use: Marsh SE (2021) "Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing" <doi:10.5281/zenodo.5706430> RRID:SCR_024675.
Maintained by Samuel Marsh. Last updated 3 months ago.
customizationggplot2scrna-seqseuratsingle-cellsingle-cell-genomicssingle-cell-rna-seqvisualization
8.6 match 242 stars 8.75 score 1.1k scripts
renkun-ken
rlist:A Toolbox for Non-Tabular Data Manipulation
Provides a set of functions for data manipulation with list objects, including mapping, filtering, grouping, sorting, updating, searching, and other useful functions. Most functions are designed to be pipeline friendly so that data processing with lists can be chained.
Maintained by Kun Ren. Last updated 2 years ago.
5.4 match 206 stars 13.73 score 2.2k scripts 123 dependents
chr1swallace
coloc:Colocalisation Tests of Two Genetic Traits
Performs the colocalisation tests described in Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020) <doi:10.1371/journal.pgen.1008720>, Wallace (2021) <doi:10.1371/journal.pgen.1009440>.
Maintained by Chris Wallace. Last updated 4 months ago.
6.1 match 162 stars 12.23 score 916 scripts 3 dependentsbioc
iClusterPlus:Integrative clustering of multi-type genomic data
Integrative clustering of multiple genomic data using a joint latent variable model.
Maintained by Qianxing Mo. Last updated 4 months ago.
multi-omicsclusteringfortranopenblas
12.9 match 5.76 score 190 scripts
inlabru-org
inlabru:Bayesian Latent Gaussian Modelling using INLA and Extensions
Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.
Maintained by Finn Lindgren. Last updated 11 hours ago.
5.9 match 96 stars 12.61 score 832 scripts 6 dependents
gforge
Gmisc:Descriptive Statistics, Transition Plots, and More
Tools for making the descriptive "Table 1" used in medical articles, a transition plot for showing changes between categories (also known as a Sankey diagram), flow charts by extending the grid package, a method for variable selection based on the SVD, Bรฉzier lines with arrows complementing the ones in the 'grid' package, and more.
Maintained by Max Gordon. Last updated 2 years ago.
7.1 match 50 stars 10.40 score 233 scripts 2 dependents
therneau
survival:Survival Analysis
Contains the core survival analysis routines, including definition of Surv objects, Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, and parametric accelerated failure time models.
Maintained by Terry M Therneau. Last updated 3 months ago.
3.6 match 400 stars 20.43 score 29k scripts 3.9k dependents
zachcp
msaR:Multiple Sequence Alignment for R Shiny
Visualises multiple sequence alignments dynamically within the Shiny web application framework.
Maintained by Zachary Charlop-Powers. Last updated 3 years ago.
alignmenthtmlwidgetsmultiplesequence
13.6 match 8 stars 5.37 score 58 scripts
keaven
gsDesign:Group Sequential Design
Derives group sequential clinical trial designs and describes their properties. Particular focus on time-to-event, binary, and continuous outcomes. Largely based on methods described in Jennison, Christopher and Turnbull, Bruce W., 2000, "Group Sequential Methods with Applications to Clinical Trials" ISBN: 0-8493-0316-8.
Maintained by Keaven Anderson. Last updated 13 days ago.
biostatisticsboundariesclinical-trialsdesignspending-functions
5.5 match 51 stars 13.05 score 338 scripts 5 dependentscran
mgcv:Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Maintained by Simon Wood. Last updated 1 years ago.
5.7 match 32 stars 12.71 score 17k scripts 7.8k dependentsbusiness-science
modeltime:The Tidymodels Extension for Time Series Modeling
The time series forecasting framework for use with the 'tidymodels' ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" (<https://otexts.com/fpp2/>). Refer to "Prophet: forecasting at scale" (<https://research.facebook.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Maintained by Matt Dancho. Last updated 5 months ago.
arimadata-sciencedeep-learningetsforecastingmachine-learningmachine-learning-algorithmsmodeltimeprophettbatstidymodelingtidymodelstimetime-seriestime-series-analysistimeseriestimeseries-forecasting
6.8 match 549 stars 10.57 score 1.1k scripts 7 dependents
revelle
psychTools:Tools to Accompany the 'psych' Package for Psychological Research
Support functions, data sets, and vignettes for the 'psych' package. Contains several of the biggest data sets for the 'psych' package as well as four vignettes. A few helper functions for file manipulation are included as well. For more information, see the <https://personality-project.org/r/> web page.
Maintained by William Revelle. Last updated 12 months ago.
12.2 match 5.89 score 178 scripts 5 dependents
gasparl
POSSA:Power Simulation for Sequential Analyses and Multiple Hypotheses
Calculates, via simulation, power and appropriate stopping alpha boundaries (and/or futility bounds) for sequential analyses (i.e., group sequential design) as well as for multiple hypotheses (multiple tests included in an analysis), given any specified global error rate. This enables the sequential use of practically any significance test, as long as the underlying data can be simulated in advance to a reasonable approximation. Lukรกcs (2022) <doi:10.21105/joss.04643>.
Maintained by Gรกspรกr Lukรกcs. Last updated 2 years ago.
multiple-testingr-pkgsequential-analysessequential-designstatistical-analysis
16.6 match 1 stars 4.30 score 3 scripts
stocnet
ERPM:Exponential Random Partition Models
Simulates and estimates the Exponential Random Partition Model presented in the paper Hoffman, Block, and Snijders (2023) <doi:10.1177/00811750221145166>. It can also be used to estimate longitudinal partitions, following the model proposed in Hoffman and Chabot (2023) <doi:10.1016/j.socnet.2023.04.002>. The model is an exponential family distribution on the space of partitions (sets of non-overlapping groups) and is called in reference to the Exponential Random Graph Models (ERGM) for networks.
Maintained by Marion Hoffman. Last updated 10 months ago.
14.9 match 10 stars 4.78 score
tdjorgensen
lavaan.mi:Fit Structural Equation Models to Multiply Imputed Data
The primary purpose of 'lavaan.mi' is to extend the functionality of the R package 'lavaan', which implements structural equation modeling (SEM). When incomplete data have been multiply imputed, the imputed data sets can be analyzed by 'lavaan' using complete-data estimation methods, but results must be pooled across imputations (Rubin, 1987, <doi:10.1002/9780470316696>). The 'lavaan.mi' package automates the pooling of point and standard-error estimates, as well as a variety of test statistics, using a familiar interface that allows users to fit an SEM to multiple imputations as they would to a single data set using the 'lavaan' package.
Maintained by Terrence D. Jorgensen. Last updated 6 days ago.
13.1 match 3 stars 5.45 score
sbg
sevenbridges2:The 'Seven Bridges Platform' API Client
R client and utilities for 'Seven Bridges Platform' API, from 'Cancer Genomics Cloud' to other 'Seven Bridges' supported platforms. API documentation is hosted publicly at <https://docs.sevenbridges.com/docs/the-api>.
Maintained by Marko Trifunovic. Last updated 21 days ago.
api-clientbioinformaticscloudsevenbridges
12.1 match 2 stars 5.90 score 4 scripts
r-lib
cli:Helpers for Developing Command Line Interfaces
A suite of tools to build attractive command line interfaces ('CLIs'), from semantic elements: headings, lists, alerts, paragraphs, etc. Supports custom themes via a 'CSS'-like language. It also contains a number of lower level 'CLI' elements: rules, boxes, trees, and 'Unicode' symbols with 'ASCII' alternatives. It support ANSI colors and text styles as well.
Maintained by Gรกbor Csรกrdi. Last updated 14 hours ago.
3.7 match 664 stars 19.34 score 1.4k scripts 14k dependents
r-spatial
stars:Spatiotemporal Arrays, Raster and Vector Data Cubes
Reading, manipulating, writing and plotting spatiotemporal arrays (raster and vector data cubes) in 'R', using 'GDAL' bindings provided by 'sf', and 'NetCDF' bindings by 'ncmeta' and 'RNetCDF'.
Maintained by Edzer Pebesma. Last updated 1 months ago.
3.9 match 571 stars 18.27 score 7.2k scripts 137 dependentsinsightsengineering
teal:Exploratory Web Apps for Analyzing Clinical Trials Data
A 'shiny' based interactive exploration framework for analyzing clinical trials data. 'teal' currently provides a dynamic filtering facility and different data viewers. 'teal' 'shiny' applications are built using standard 'shiny' modules.
Maintained by Dawid Kaledkowski. Last updated 22 days ago.
clinical-trialsnestshinywebapp
5.6 match 197 stars 12.68 score 176 scripts 5 dependentsr-lib
scales:Scale Functions for Visualization
Graphical scales map data to aesthetics, and provide methods for automatically determining breaks and labels for axes and legends.
Maintained by Thomas Lin Pedersen. Last updated 5 months ago.
3.5 match 419 stars 19.88 score 88k scripts 7.9k dependents
nacnudus
unpivotr:Unpivot Complex and Irregular Data Layouts
Tools for converting data from complex or irregular layouts to a columnar structure. For example, tables with multilevel column or row headers, or spreadsheets. Header and data cells are selected by their contents and position, as well as formatting and comments where available, and are associated with one other by their proximity in given directions. Functions for data frames and HTML tables are provided.
Maintained by Duncan Garmonsway. Last updated 1 months ago.
6.8 match 186 stars 10.35 score 368 scripts 3 dependentsropensci
jagstargets:Targets for JAGS Pipelines
Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'jagstargets' R package is leverages 'targets' and 'R2jags' to ease this burden. 'jagstargets' makes it super easy to set up scalable JAGS pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. For the underlying methodology, please refer to the documentation of 'targets' <doi:10.21105/joss.02959> and 'JAGS' (Plummer 2003) <https://www.r-project.org/conferences/DSC-2003/Proceedings/Plummer.pdf>.
Maintained by William Michael Landau. Last updated 3 months ago.
bayesianhigh-performance-computingjagsmaker-targetopiareproducibilityrjagsstatisticstargetscpp
9.9 match 10 stars 7.01 score 32 scriptsbioc
edgeR:Empirical Analysis of Digital Gene Expression Data in R
Differential expression analysis of sequence count data. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models, quasi-likelihood, and gene set enrichment. Can perform differential analyses of any type of omics data that produces read counts, including RNA-seq, ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral counts. RNA-seq analyses can be conducted at the gene or isoform level, and tests can be conducted for differential exon or transcript usage.
Maintained by Yunshun Chen. Last updated 7 days ago.
alternativesplicingbatcheffectbayesianbiomedicalinformaticscellbiologychipseqclusteringcoveragedifferentialexpressiondifferentialmethylationdifferentialsplicingdnamethylationepigeneticsfunctionalgenomicsgeneexpressiongenesetenrichmentgeneticsimmunooncologymultiplecomparisonnormalizationpathwaysproteomicsqualitycontrolregressionrnaseqsagesequencingsinglecellsystemsbiologytimecoursetranscriptiontranscriptomicsopenblas
5.2 match 13.40 score 17k scripts 255 dependentsbioc
canceR:A Graphical User Interface for accessing and modeling the Cancer Genomics Data of MSKCC
The package is user friendly interface based on the cgdsr and other modeling packages to explore, compare, and analyse all available Cancer Data (Clinical data, Gene Mutation, Gene Methylation, Gene Expression, Protein Phosphorylation, Copy Number Alteration) hosted by the Computational Biology Center at Memorial-Sloan-Kettering Cancer Center (MSKCC).
Maintained by Karim Mezhoud. Last updated 5 months ago.
guigeneexpressionclusteringgogenesetenrichmentkeggmultiplecomparisoncancercancer-datagenegene-expressiongene-methylationgene-mutationgene-setsmethylationmskccmutationstcltk
13.2 match 7 stars 5.25 score 17 scripts
hadley
plyr:Tools for Splitting, Applying and Combining Data
A set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to fit a model to each spatial location or time point in your study, summarise data by panels or collapse high-dimensional arrays to simpler summary statistics. The development of 'plyr' has been generously supported by 'Becton Dickinson'.
Maintained by Hadley Wickham. Last updated 4 months ago.
3.8 match 500 stars 18.16 score 83k scripts 3.3k dependents
plotly
plotly:Create Interactive Web Graphics via 'plotly.js'
Create interactive web graphics from 'ggplot2' graphs and/or a custom interface to the (MIT-licensed) JavaScript library 'plotly.js' inspired by the grammar of graphics.
Maintained by Carson Sievert. Last updated 3 months ago.
d3jsdata-visualizationggplot2javascriptplotlyshinywebgl
3.5 match 2.6k stars 19.43 score 93k scripts 797 dependents
polkas
miceFast:Fast Imputations Using 'Rcpp' and 'Armadillo'
Fast imputations under the object-oriented programming paradigm. Moreover there are offered a few functions built to work with popular R packages such as 'data.table' or 'dplyr'. The biggest improvement in time performance could be achieve for a calculation where a grouping variable have to be used. A single evaluation of a quantitative model for the multiple imputations is another major enhancement. A new major improvement is one of the fastest predictive mean matching in the R world because of presorting and binary search.
Maintained by Maciej Nasinski. Last updated 1 months ago.
cppfastfast-imputationsgroupingimputationimputationsmatrixmromultiple-imputationrcpprcpparmadillovifweightingopenblascppopenmp
11.6 match 20 stars 5.94 score 29 scriptstidyverse
stringr:Simple, Consistent Wrappers for Common String Operations
A consistent, simple and easy to use set of wrappers around the fantastic 'stringi' package. All function and argument names (and positions) are consistent, all functions deal with "NA"'s and zero length vectors in the same way, and the output from one function is easy to feed into the input of another.
Maintained by Hadley Wickham. Last updated 7 months ago.
3.1 match 628 stars 21.99 score 164k scripts 8.3k dependents
chrisaberson
pwr2ppl:Power Analyses for Common Designs (Power to the People)
Statistical power analysis for designs including t-tests, correlations, multiple regression, ANOVA, mediation, and logistic regression. Functions accompany Aberson (2019) <doi:10.4324/9781315171500>.
Maintained by Chris Aberson. Last updated 3 years ago.
16.5 match 17 stars 4.16 score 17 scriptsbioc
mogsa:Multiple omics data integrative clustering and gene set analysis
This package provide a method for doing gene set analysis based on multiple omics data.
Maintained by Chen Meng. Last updated 5 months ago.
geneexpressionprincipalcomponentstatisticalmethodclusteringsoftware
16.0 match 4.29 score 49 scripts
robjhyndman
forecast:Forecasting Functions for Time Series and Linear Models
Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
Maintained by Rob Hyndman. Last updated 7 months ago.
forecastforecastingopenblascpp
3.7 match 1.1k stars 18.63 score 16k scripts 239 dependents
richarddmorey
BayesFactor:Computation of Bayes Factors for Common Designs
A suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one-way designs, general ANOVA designs, and linear regression.
Maintained by Richard D. Morey. Last updated 1 years ago.
5.0 match 133 stars 13.70 score 1.7k scripts 21 dependents
dppalomar
portfolioBacktest:Automated Backtesting of Portfolios over Multiple Datasets
Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots.
Maintained by Daniel P. Palomar. Last updated 3 years ago.
backtestingfinancial-marketsportfolio
10.1 match 60 stars 6.60 score 66 scripts
stamats
MKinfer:Inferential Statistics
Computation of various confidence intervals (Altman et al. (2000), ISBN:978-0-727-91375-3; Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) including bootstrapped versions (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) as well as Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2), permutation (Janssen (1997), <doi:10.1016/S0167-7152(97)00043-6>), bootstrap (Davison and Hinkley (1997), ISBN:978-0-511-80284-3), intersection-union (Sozu et al. (2015), ISBN:978-3-319-22005-5) and multiple imputation (Barnard and Rubin (1999), <doi:10.1093/biomet/86.4.948>) t-test; furthermore, computation of intersection-union z-test as well as multiple imputation Wilcoxon tests. Graphical visualization by volcano and Bland-Altman plots (Bland and Altman (1986), <doi:10.1016/S0140-6736(86)90837-8>; Shieh (2018), <doi:10.1186/s12874-018-0505-y>).
Maintained by Matthias Kohl. Last updated 12 months ago.
10.1 match 6 stars 6.56 score 71 scripts 4 dependents
juba
questionr:Functions to Make Surveys Processing Easier
Set of functions to make the processing and analysis of surveys easier : interactive shiny apps and addins for data recoding, contingency tables, dataset metadata handling, and several convenience functions.
Maintained by Julien Barnier. Last updated 10 hours ago.
5.1 match 83 stars 12.91 score 1.1k scripts 19 dependents
sjmack
HLAtools:Toolkit for HLA Immunogenomics
A toolkit for the analysis and management of data for genes in the so-called "Human Leukocyte Antigen" (HLA) region. Functions extract reference data from the Anthony Nolan HLA Informatics Group/ImmunoGeneTics HLA 'GitHub' repository (ANHIG/IMGTHLA) <https://github.com/ANHIG/IMGTHLA>, validate Genotype List (GL) Strings, convert between UNIFORMAT and GL String Code (GLSC) formats, translate HLA alleles and GLSCs across ImmunoPolymorphism Database (IPD) IMGT/HLA Database release versions, identify differences between pairs of alleles at a locus, generate customized, multi-position sequence alignments, trim and convert allele-names across nomenclature epochs, and extend existing data-analysis methods.
Maintained by Steven Mack. Last updated 14 days ago.
10.6 match 4 stars 6.21 score 7 scripts 1 dependents
egeminiani
penfa:Single- And Multiple-Group Penalized Factor Analysis
Fits single- and multiple-group penalized factor analysis models via a trust-region algorithm with integrated automatic multiple tuning parameter selection (Geminiani et al., 2021 <doi:10.1007/s11336-021-09751-8>). Available penalties include lasso, adaptive lasso, scad, mcp, and ridge.
Maintained by Elena Geminiani. Last updated 4 years ago.
factor-analysislassolatent-variablesmultiple-groupoptimizationpenalizationpsychometrics
14.7 match 3 stars 4.48 score 5 scripts
gabrielgesteira
qtlpoly:Random-Effect Multiple QTL Mapping in Autopolyploids
Performs random-effect multiple interval mapping (REMIM) in full-sib families of autopolyploid species based on restricted maximum likelihood (REML) estimation and score statistics, as described in Pereira et al. (2020) <doi:10.1534/genetics.120.303080>.
Maintained by Gabriel de Siqueira Gesteira. Last updated 4 months ago.
polyploidqtl-mappingopenblascppopenmp
12.7 match 6 stars 5.17 score 61 scripts
stemangiola
tidyseurat:Brings Seurat to the Tidyverse
It creates an invisible layer that allow to see the 'Seurat' object as tibble and interact seamlessly with the tidyverse.
Maintained by Stefano Mangiola. Last updated 8 months ago.
assaydomaininfrastructurernaseqdifferentialexpressiongeneexpressionnormalizationclusteringqualitycontrolsequencingtranscriptiontranscriptomicsdplyrggplot2pcapurrrsctseuratsingle-cellsingle-cell-rna-seqtibbletidyrtidyversetranscriptstsneumap
6.8 match 158 stars 9.66 score 398 scripts 1 dependentsbioc
psichomics:Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation
Interactive R package with an intuitive Shiny-based graphical interface for alternative splicing quantification and integrative analyses of alternative splicing and gene expression based on The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx), Sequence Read Archive (SRA) and user-provided data. The tool interactively performs survival, dimensionality reduction and median- and variance-based differential splicing and gene expression analyses that benefit from the incorporation of clinical and molecular sample-associated features (such as tumour stage or survival). Interactive visual access to genomic mapping and functional annotation of selected alternative splicing events is also included.
Maintained by Nuno Saraiva-Agostinho. Last updated 5 months ago.
sequencingrnaseqalternativesplicingdifferentialsplicingtranscriptionguiprincipalcomponentsurvivalbiomedicalinformaticstranscriptomicsimmunooncologyvisualizationmultiplecomparisongeneexpressiondifferentialexpressionalternative-splicingbioconductordata-analysesdifferential-gene-expressiondifferential-splicing-analysisgene-expressiongtexrecount2rna-seq-datasplicing-quantificationsratcgavast-toolscpp
9.4 match 36 stars 6.95 score 31 scriptsuupharmacometrics
xpose:Diagnostics for Pharmacometric Models
Diagnostics for non-linear mixed-effects (population) models from 'NONMEM' <https://www.iconplc.com/solutions/technologies/nonmem/>. 'xpose' facilitates data import, creation of numerical run summary and provide 'ggplot2'-based graphics for data exploration and model diagnostics.
Maintained by Benjamin Guiastrennec. Last updated 2 months ago.
diagnosticsggplot2nonmempharmacometricsxpose
5.9 match 62 stars 11.02 score 183 scripts 6 dependents
statistikat
VIM:Visualization and Imputation of Missing Values
New tools for the visualization of missing and/or imputed values are introduced, which can be used for exploring the data and the structure of the missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods may help to identify the mechanism generating the missing values and allows to explore the data including missing values. In addition, the quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot methods. A graphical user interface available in the separate package VIMGUI allows an easy handling of the implemented plot methods.
Maintained by Matthias Templ. Last updated 7 months ago.
hotdeckimputation-methodsmodel-predictionsvisualizationcpp
4.5 match 85 stars 14.44 score 2.6k scripts 19 dependentsbusiness-science
sweep:Tidy Tools for Forecasting
Tidies up the forecasting modeling and prediction work flow, extends the 'broom' package with 'sw_tidy', 'sw_glance', 'sw_augment', and 'sw_tidy_decomp' functions for various forecasting models, and enables converting 'forecast' objects to "tidy" data frames with 'sw_sweep'.
Maintained by Matt Dancho. Last updated 1 years ago.
broomforecastforecasting-modelspredictiontidytidyversetimetime-seriestimeseries
7.0 match 155 stars 9.26 score 399 scripts 1 dependents
jwb133
smcfcs:Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
Implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.
Maintained by Jonathan Bartlett. Last updated 3 days ago.
7.2 match 11 stars 9.00 score 59 scripts 1 dependents
nepem-ufsc
pliman:Tools for Plant Image Analysis
Tools for both single and batch image manipulation and analysis (Olivoto, 2022 <doi:10.1111/2041-210X.13803>) and phytopathometry (Olivoto et al., 2022 <doi:10.1007/S40858-021-00487-5>). The tools can be used for the quantification of leaf area, object counting, extraction of image indexes, shape measurement, object landmark identification, and Elliptical Fourier Analysis of object outlines (Claude (2008) <doi:10.1007/978-0-387-77789-4>). The package also provides a comprehensive pipeline for generating shapefiles with complex layouts and supports high-throughput phenotyping of RGB, multispectral, and hyperspectral orthomosaics. This functionality facilitates field phenotyping using UAV- or satellite-based imagery.
Maintained by Tiago Olivoto. Last updated 20 hours ago.
9.6 match 10 stars 6.70 score 476 scriptsmjskay
tidybayes:Tidy Data and 'Geoms' for Bayesian Models
Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.
Maintained by Matthew Kay. Last updated 6 months ago.
bayesian-data-analysisbrmsggplot2jagsstantidy-datavisualization
4.3 match 733 stars 14.72 score 7.3k scripts 20 dependents
yihui
xfun:Supporting Functions for Packages Maintained by 'Yihui Xie'
Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
Maintained by Yihui Xie. Last updated 4 days ago.
3.5 match 145 stars 18.18 score 916 scripts 4.4k dependents
mikewlcheung
metaSEM:Meta-Analysis using Structural Equation Modeling
A collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the 'OpenMx' and 'lavaan' packages. It also implements various procedures to perform meta-analytic structural equation modeling on the correlation and covariance matrices, see Cheung (2015) <doi:10.3389/fpsyg.2014.01521>.
Maintained by Mike Cheung. Last updated 11 days ago.
meta-analysismeta-analytic-semmissing-datamultilevel-modelsmultivariate-analysisstructural-equation-modelingstructural-equation-models
6.8 match 30 stars 9.43 score 208 scripts 1 dependents