Showing 200 of total 3016 results (show query)
easystats
effectsize:Indices of Effect Size
Provide utilities to work with indices of effect size for a wide variety of models and hypothesis tests (see list of supported models using the function 'insight::supported_models()'), allowing computation of and conversion between indices such as Cohen's d, r, odds, etc. References: Ben-Shachar et al. (2020) <doi:10.21105/joss.02815>.
Maintained by Mattan S. Ben-Shachar. Last updated 1 months ago.
anovacohens-dcomputeconversioncorrelationeffect-sizeeffectsizehacktoberfesthedges-ginterpretationstandardizationstandardizedstatistics
43.0 match 344 stars 16.38 score 1.8k scripts 29 dependentselvanceyhan
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.
105.1 match 5.80 score 21 scripts 2 dependentscdeager
standardize:Tools for Standardizing Variables for Regression in R
Tools which allow regression variables to be placed on similar scales, offering computational benefits as well as easing interpretation of regression output.
Maintained by Christopher D. Eager. Last updated 4 years ago.
83.8 match 23 stars 6.50 score 92 scripts 1 dependentsdfsp-spirit
fsbrain:Managing and Visualizing Brain Surface Data
Provides high-level access to neuroimaging data from standard software packages like 'FreeSurfer' <http://freesurfer.net/> on the level of subjects and groups. Load morphometry data, surfaces and brain parcellations based on atlases. Mask data using labels, load data for specific atlas regions only, and visualize data and statistical results directly in 'R'.
Maintained by Tim Schäfer. Last updated 4 months ago.
3dbraindtifreesurfermeshmrineuroimagingresearchsurfacevisualizationvoxel
66.0 match 66 stars 6.47 score 15 scriptseasystats
parameters:Processing of Model Parameters
Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).
Maintained by Daniel Lüdecke. Last updated 2 days ago.
betabootstrapciconfidence-intervalsdata-reductioneasystatsfafeature-extractionfeature-reductionhacktoberfestparameterspcapvaluesregression-modelsrobust-statisticsstandardizestandardized-estimatesstatistical-models
24.0 match 453 stars 15.65 score 1.8k scripts 56 dependentsglenndavis52
colorSpec:Color Calculations with Emphasis on Spectral Data
Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners. Build complex systems from simpler parts using a spectral product algebra. For light sources, compute CCT, CRI, SSI, and IES TM-30 reports. For object colors, compute optimal colors and Logvinenko coordinates. Work with the standard CIE illuminants and color matching functions, and read spectra from text files, including CGATS files. Estimate a spectrum from its response. A user guide and 9 vignettes are included.
Maintained by Glenn Davis. Last updated 1 months ago.
48.8 match 2 stars 6.34 score 73 scripts 5 dependentssfcheung
stdmod:Standardized Moderation Effect and Its Confidence Interval
Functions for computing a standardized moderation effect in moderated regression and forming its confidence interval by nonparametric bootstrapping as proposed in Cheung, Cheung, Lau, Hui, and Vong (2022) <doi:10.1037/hea0001188>. Also includes simple-to-use functions for computing conditional effects (unstandardized or standardized) and plotting moderation effects.
Maintained by Shu Fai Cheung. Last updated 6 months ago.
bootstrappingconfidence-intervaleffect-sizesmoderationregressionstandardizationstandardized-moderation
50.4 match 1 stars 5.62 score 46 scriptsropensci
gigs:Assess Fetal, Newborn, and Child Growth with International Standards
Convert between anthropometric measures and z-scores/centiles in multiple growth standards, and classify fetal, newborn, and child growth accordingly. With a simple interface to growth standards from the World Health Organisation and International Fetal and Newborn Growth Consortium for the 21st Century, gigs makes growth assessment easy and reproducible for clinicians, researchers and policy-makers.
Maintained by Simon R Parker. Last updated 25 days ago.
anthropometrygrowth-standardsintergrowthwho
62.9 match 4 stars 4.38 score 8 scriptslrberge
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.
17.4 match 387 stars 14.69 score 3.8k scripts 25 dependentsropengov
rqog:Download data from the Quality of Government Institute data
R client for the Quality of Government (QOG) open data. Client can be used to fetch data files <https://qog.pol.gu.se/data> and converted into data.frame objects in R.
Maintained by Markus Kainu. Last updated 2 years ago.
53.3 match 15 stars 4.22 score 22 scriptsalanarnholt
BSDA:Basic Statistics and Data Analysis
Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.
Maintained by Alan T. Arnholt. Last updated 2 years ago.
23.5 match 7 stars 9.11 score 1.3k scripts 6 dependentshadley
lazyeval:Lazy (Non-Standard) Evaluation
An alternative approach to non-standard evaluation using formulas. Provides a full implementation of LISP style 'quasiquotation', making it easier to generate code with other code.
Maintained by Hadley Wickham. Last updated 3 years ago.
12.5 match 131 stars 15.74 score 520 scripts 1.8k dependentskkholst
mets:Analysis of Multivariate Event Times
Implementation of various statistical models for multivariate event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>. Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray, Ghosh-Lin, Binomial regression) with fast computation of influence functions.
Maintained by Klaus K. Holst. Last updated 3 days ago.
multivariate-time-to-eventsurvival-analysistime-to-eventfortranopenblascpp
14.3 match 14 stars 13.47 score 236 scripts 42 dependentssizespectrum
mizer:Dynamic Multi-Species Size Spectrum Modelling
A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.
Maintained by Gustav Delius. Last updated 2 months ago.
ecosystem-modelfish-population-dynamicsfisheriesfisheries-managementmarine-ecosystempopulation-dynamicssimulationsize-structurespecies-interactionstransport-equationcpp
20.0 match 38 stars 9.43 score 207 scriptsdewittpe
pedbp:Pediatric Blood Pressure
Data and utilities for estimating pediatric blood pressure percentiles by sex, age, and optionally height (stature) as described in Martin et.al. (2022) <doi:10.1001/jamanetworkopen.2022.36918>. Blood pressure percentiles for children under one year of age come from Gemelli et.al. (1990) <doi:10.1007/BF02171556>. Estimates of blood pressure percentiles for children at least one year of age are informed by data from the National Heart, Lung, and Blood Institute (NHLBI) and the Centers for Disease Control and Prevention (CDC) <doi:10.1542/peds.2009-2107C> or from Lo et.al. (2013) <doi:10.1542/peds.2012-1292>. The flowchart for selecting the informing data source comes from Martin et.al. (2022) <doi:10.1542/hpeds.2021-005998>.
Maintained by Peter DeWitt. Last updated 2 months ago.
blood-pressuregrowth-standardspediatriccpp
28.7 match 6 stars 6.43 score 45 scriptsjacob-long
jtools:Analysis and Presentation of Social Scientific Data
This is a collection of tools for more efficiently understanding and sharing the results of (primarily) regression analyses. There are also a number of miscellaneous functions for statistical and programming purposes. Support for models produced by the survey and lme4 packages are points of emphasis.
Maintained by Jacob A. Long. Last updated 6 months ago.
12.7 match 167 stars 14.48 score 4.0k scripts 14 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.
11.3 match 222 stars 15.93 score 4.8k scripts 20 dependentsopendendro
dplR:Dendrochronology Program Library in R
Perform tree-ring analyses such as detrending, chronology building, and cross dating. Read and write standard file formats used in dendrochronology.
Maintained by Andy Bunn. Last updated 19 days ago.
15.1 match 39 stars 11.71 score 546 scripts 26 dependentsmartin3141
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 30 days ago.
brainmrimrsmrshubspectroscopyfortran
19.1 match 25 stars 8.52 score 81 scriptskosukeimai
MatchIt:Nonparametric Preprocessing for Parametric Causal Inference
Selects matched samples of the original treated and control groups with similar covariate distributions -- can be used to match exactly on covariates, to match on propensity scores, or perform a variety of other matching procedures. The package also implements a series of recommendations offered in Ho, Imai, King, and Stuart (2007) <DOI:10.1093/pan/mpl013>. (The 'gurobi' package, which is not on CRAN, is optional and comes with an installation of the Gurobi Optimizer, available at <https://www.gurobi.com>.)
Maintained by Noah Greifer. Last updated 2 days ago.
10.8 match 220 stars 15.03 score 2.4k scripts 21 dependentsrpolars
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 3 days ago.
13.3 match 499 stars 12.01 score 1.0k scripts 2 dependentsdgbonett
vcmeta:Varying Coefficient Meta-Analysis
Implements functions for varying coefficient meta-analysis methods. These methods do not assume effect size homogeneity. Subgroup effect size comparisons, general linear effect size contrasts, and linear models of effect sizes based on varying coefficient methods can be used to describe effect size heterogeneity. Varying coefficient meta-analysis methods do not require the unrealistic assumptions of the traditional fixed-effect and random-effects meta-analysis methods. For details see: Statistical Methods for Psychologists, Volume 5, <https://dgbonett.sites.ucsc.edu/>.
Maintained by Douglas G. Bonett. Last updated 8 months ago.
51.8 match 1 stars 3.00 score 8 scriptssachsmc
stdReg2:Regression Standardization for Causal Inference
Contains more modern tools for causal inference using regression standardization. Four general classes of models are implemented; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models, and shared frailty gamma-Weibull models. Methodological details are described in Sjölander, A. (2016) <doi:10.1007/s10654-016-0157-3>. Also includes functionality for doubly robust estimation for generalized linear models in some special cases, and the ability to implement custom models.
Maintained by Michael C Sachs. Last updated 16 days ago.
30.5 match 2 stars 5.08 score 9 scriptsacdelre
MAd:Meta-Analysis with Mean Differences
A collection of functions for conducting a meta-analysis with mean differences data. It uses recommended procedures as described in The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).
Maintained by AC Del Re. Last updated 3 years ago.
34.3 match 4.29 score 82 scripts 2 dependentspln-team
PLNmodels:Poisson Lognormal Models
The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 <doi:10.3389/fevo.2021.588292>) can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data, discriminant analysis, model-based clustering and network inference. Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.
Maintained by Julien Chiquet. Last updated 4 days ago.
count-datamultivariate-analysisnetwork-inferencepcapoisson-lognormal-modelopenblascpp
15.0 match 56 stars 9.50 score 226 scriptsdgbonett
statpsych:Statistical Methods for Psychologists
Implements confidence interval and sample size methods that are especially useful in psychological research. The methods can be applied in 1-group, 2-group, paired-samples, and multiple-group designs and to a variety of parameters including means, medians, proportions, slopes, standardized mean differences, standardized linear contrasts of means, plus several measures of correlation and association. Confidence interval and sample size functions are given for single parameters as well as differences, ratios, and linear contrasts of parameters. The sample size functions can be used to approximate the sample size needed to estimate a parameter or function of parameters with desired confidence interval precision or to perform a variety of hypothesis tests (directional two-sided, equivalence, superiority, noninferiority) with desired power. For details see: Statistical Methods for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.
Maintained by Douglas G. Bonett. Last updated 3 months ago.
29.5 match 6 stars 4.83 score 15 scripts 1 dependentsjeksterslab
betaSandwich:Robust Confidence Intervals for Standardized Regression Coefficients
Generates robust confidence intervals for standardized regression coefficients using heteroskedasticity-consistent standard errors for models fitted by lm() as described in Dudgeon (2017) <doi:10.1007/s11336-017-9563-z>. The package can also be used to generate confidence intervals for R-squared, adjusted R-squared, and differences of standardized regression coefficients. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.
confidence-intervalsheteroskedasticity-consistent-standard-errorsstandardized-regression-coefficients
34.2 match 4.16 score 16 scriptsalexkowa
EnvStats:Package for Environmental Statistics, Including US EPA Guidance
Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <doi:10.1007/978-1-4614-8456-1>).
Maintained by Alexander Kowarik. Last updated 17 days ago.
10.9 match 26 stars 12.80 score 2.4k scripts 46 dependentscorentinjgosling
metaConvert:An Automatic Suite for Estimation of Various Effect Size Measures
Automatically estimate 11 effect size measures from a well-formatted dataset. Various other functions can help, for example, removing dependency between several effect sizes, or identifying differences between two datasets. This package is mainly designed to assist in conducting a systematic review with a meta-analysis but can be useful to any researcher interested in estimating an effect size.
Maintained by Corentin J. Gosling. Last updated 4 months ago.
43.9 match 3.18 score 3 scriptsbradyajohnston
standard:Simplified Fitting and Use of Standard Curves
{standard} provices a more simplified interface to the linear models system in R for the fitting of standard curves and their usage in biochemistry and molecular biology.
Maintained by Brady Johnston. Last updated 1 years ago.
69.7 match 1.98 score 19 scriptstbates
umx:Structural Equation Modeling and Twin Modeling in R
Quickly create, run, and report structural equation models, and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS. Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. Twin Research and Human Genetics, 22, 27-41. <doi:10.1017/thg.2019.2>.
Maintained by Timothy C. Bates. Last updated 2 days ago.
behavior-geneticsgeneticsopenmxpsychologysemstatisticsstructural-equation-modelingtutorialstwin-modelsumx
14.6 match 44 stars 9.45 score 472 scriptsstan-dev
posterior:Tools for Working with Posterior Distributions
Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) <doi:10.1214/20-BA1221>.
Maintained by Paul-Christian Bürkner. Last updated 10 days ago.
8.4 match 168 stars 16.13 score 3.3k scripts 342 dependentstomasfryda
h2o:R Interface for the 'H2O' Scalable Machine Learning Platform
R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection, Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).
Maintained by Tomas Fryda. Last updated 1 years ago.
16.5 match 3 stars 8.20 score 7.8k scripts 11 dependentsradiant-rstats
radiant.data:Data Menu for Radiant: Business Analytics using R and Shiny
The Radiant Data menu includes interfaces for loading, saving, viewing, visualizing, summarizing, transforming, and combining data. It also contains functionality to generate reproducible reports of the analyses conducted in the application.
Maintained by Vincent Nijs. Last updated 5 months ago.
16.3 match 54 stars 8.30 score 146 scripts 6 dependentsmrcieu
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 10 days ago.
11.8 match 467 stars 11.23 score 1.7k scripts 1 dependentsflorianhartig
BayesianTools:General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics
General-purpose MCMC and SMC samplers, as well as plots and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.
Maintained by Florian Hartig. Last updated 1 years ago.
bayesecological-modelsmcmcoptimizationsmcsystems-biologycpp
12.9 match 122 stars 10.17 score 580 scripts 5 dependentsjeksterslab
betaDelta:Confidence Intervals for Standardized Regression Coefficients
Generates confidence intervals for standardized regression coefficients using delta method standard errors for models fitted by lm() as described in Yuan and Chan (2011) <doi:10.1007/s11336-011-9224-6> and Jones and Waller (2015) <doi:10.1007/s11336-013-9380-y>. The package can also be used to generate confidence intervals for differences of standardized regression coefficients and as a general approach to performing the delta method. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.
confidence-intervalsdelta-method-standard-errorsstandardized-regression-coefficients
31.1 match 4.20 score 20 scriptsphilchalmers
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 19 hours ago.
monte-carlo-simulationsimulationsimulation-framework
9.5 match 62 stars 13.36 score 253 scripts 46 dependentsswissstatsr
dcatapchr:Create DCAT-AP CH Metadata Files
Create DCAT-AP CH metadata files, typically in rdf format.
Maintained by Sandro Burri. Last updated 3 months ago.
43.9 match 2.81 score 3 scriptsanthonychristidis
RPESE:Estimates of Standard Errors for Risk and Performance Measures
Estimates of standard errors of popular risk and performance measures for asset or portfolio returns using methods as described in Chen and Martin (2021) <doi:10.21314/JOR.2020.446>.
Maintained by Anthony Christidis. Last updated 7 months ago.
32.1 match 3.83 score 9 scriptsepiverse-trace
cleanepi:Clean and Standardize Epidemiological Data
Cleaning and standardizing tabular data package, tailored specifically for curating epidemiological data. It streamlines various data cleaning tasks that are typically expected when working with datasets in epidemiology. It returns the processed data in the same format, and generates a comprehensive report detailing the outcomes of each cleaning task.
Maintained by Karim Mané. Last updated 2 days ago.
data-cleaningepidemiologyepiverse
15.9 match 9 stars 7.44 score 19 scriptszhenkewu
baker:"Nested Partially Latent Class Models"
Provides functions to specify, fit and visualize nested partially-latent class models ( Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>; Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>; Wu and Chen (2021) <doi:10.1002/sim.8804>) for inference of population disease etiology and individual diagnosis. In the motivating Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities of interest sum to one hundred percent, the PERCH scientists frequently refer to them as population etiology pie and individual etiology pie, hence the name of the package.
Maintained by Zhenke Wu. Last updated 11 months ago.
bayesiancase-controllatent-class-analysisjagscpp
19.3 match 8 stars 6.00 score 21 scriptsrobinhankin
magic:Create and Investigate Magic Squares
A collection of functions for the manipulation and analysis of arbitrarily dimensioned arrays. The original motivation for the package was the development of efficient, vectorized algorithms for the creation and investigation of magic squares and high-dimensional magic hypercubes.
Maintained by Robin K. S. Hankin. Last updated 2 months ago.
10.1 match 3 stars 11.12 score 436 scripts 230 dependentssfcheung
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 23 days ago.
bootstrappingconfidence-intervallavaanmanymomemediationmoderated-mediationmoderationregressionsemstandardized-effect-sizestructural-equation-modeling
13.7 match 1 stars 8.06 score 172 scripts 4 dependentseblondel
ows4R:Interface to OGC Web-Services (OWS)
Provides an Interface to Web-Services defined as standards by the Open Geospatial Consortium (OGC), including Web Feature Service (WFS) for vector data, Web Coverage Service (WCS), Catalogue Service (CSW) for ISO/OGC metadata, Web Processing Service (WPS) for data processes, and associated standards such as the common web-service specification (OWS) and OGC Filter Encoding. Partial support is provided for the Web Map Service (WMS). The purpose is to add support for additional OGC service standards such as Web Coverage Processing Service (WCPS), the Sensor Observation Service (SOS), or even new standard services emerging such OGC API or SensorThings.
Maintained by Emmanuel Blondel. Last updated 1 months ago.
catalogue-servicecswdataaccessfesgeospatialisoogcowssdispatialspatial-datastandardwebfeatureservicewfs
12.0 match 38 stars 9.03 score 99 scripts 5 dependentsdvats
mcmcse:Monte Carlo Standard Errors for MCMC
Provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE computation for expectation and quantile estimators is supported as well as multivariate estimations. The package also provides functions for computing effective sample size and for plotting Monte Carlo estimates versus sample size.
Maintained by Dootika Vats. Last updated 1 months ago.
effective-sample-sizemcmcoutput-aopenblascpp
12.2 match 12 stars 8.77 score 314 scripts 17 dependentsbsvars
bsvars:Bayesian Estimation of Structural Vector Autoregressive Models
Provides fast and efficient procedures for Bayesian analysis of Structural Vector Autoregressions. This package estimates a wide range of models, including homo-, heteroskedastic, and non-normal specifications. Structural models can be identified by adjustable exclusion restrictions, time-varying volatility, or non-normality. They all include a flexible three-level equation-specific local-global hierarchical prior distribution for the estimated level of shrinkage for autoregressive and structural parameters. Additionally, the package facilitates predictive and structural analyses such as impulse responses, forecast error variance and historical decompositions, forecasting, verification of heteroskedasticity, non-normality, and hypotheses on autoregressive parameters, as well as analyses of structural shocks, volatilities, and fitted values. Beautiful plots, informative summary functions, and extensive documentation including the vignette by Woźniak (2024) <doi:10.48550/arXiv.2410.15090> complement all this. The implemented techniques align closely with those presented in Lütkepohl, Shang, Uzeda, & Woźniak (2024) <doi:10.48550/arXiv.2404.11057>, Lütkepohl & Woźniak (2020) <doi:10.1016/j.jedc.2020.103862>, and Song & Woźniak (2021) <doi:10.1093/acrefore/9780190625979.013.174>. The 'bsvars' package is aligned regarding objects, workflows, and code structure with the R package 'bsvarSIGNs' by Wang & Woźniak (2024) <doi:10.32614/CRAN.package.bsvarSIGNs>, and they constitute an integrated toolset.
Maintained by Tomasz Woźniak. Last updated 1 months ago.
bayesian-inferenceeconometricsvector-autoregressionopenblascppopenmp
13.6 match 46 stars 7.67 score 32 scripts 1 dependentssfcheung
betaselectr:Betas-Select in Structural Equation Models and Linear Models
It computes betas-select, coefficients after standardization in structural equation models and regression models, standardizing only selected variables. Supports models with moderation, with product terms formed after standardization. It also offers confidence intervals that account for standardization, including bootstrap confidence intervals as proposed by Cheung et al. (2022) <doi:10.1037/hea0001188>.
Maintained by Shu Fai Cheung. Last updated 4 months ago.
bootstrappingconfidence-intervalsgeneralized-linear-modelslavaanlogistic-regressionregressionsemstandardizationstructural-equation-modeling
21.0 match 1 stars 4.95 score 8 scriptsdarwin-eu
CodelistGenerator:Identify Relevant Clinical Codes and Evaluate Their Use
Generate a candidate code list for the Observational Medical Outcomes Partnership (OMOP) common data model based on string matching. For a given search strategy, a candidate code list will be returned.
Maintained by Edward Burn. Last updated 25 days ago.
10.5 match 13 stars 9.87 score 165 scripts 4 dependentscvxgrp
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.
8.0 match 207 stars 12.89 score 768 scripts 51 dependentssuyusung
arm:Data Analysis Using Regression and Multilevel/Hierarchical Models
Functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.
Maintained by Yu-Sung Su. Last updated 5 months ago.
8.2 match 25 stars 12.38 score 3.3k scripts 89 dependentsbioc
metaMS:MS-based metabolomics annotation pipeline
MS-based metabolomics data processing and compound annotation pipeline.
Maintained by Yann Guitton. Last updated 5 months ago.
immunooncologymassspectrometrymetabolomics
13.6 match 15 stars 7.50 score 15 scriptsbioc
KBoost:Inference of gene regulatory networks from gene expression data
Reconstructing gene regulatory networks and transcription factor activity is crucial to understand biological processes and holds potential for developing personalized treatment. Yet, it is still an open problem as state-of-art algorithm are often not able to handle large amounts of data. Furthermore, many of the present methods predict numerous false positives and are unable to integrate other sources of information such as previously known interactions. Here we introduce KBoost, an algorithm that uses kernel PCA regression, boosting and Bayesian model averaging for fast and accurate reconstruction of gene regulatory networks. KBoost can also use a prior network built on previously known transcription factor targets. We have benchmarked KBoost using three different datasets against other high performing algorithms. The results show that our method compares favourably to other methods across datasets.
Maintained by Luis F. Iglesias-Martinez. Last updated 5 months ago.
networkgraphandnetworkbayesiannetworkinferencegeneregulationtranscriptomicssystemsbiologytranscriptiongeneexpressionregressionprincipalcomponent
22.1 match 4 stars 4.60 score 9 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
9.1 match 68 stars 11.08 score 1.7k scripts 6 dependentseasystats
datawizard:Easy Data Wrangling and Statistical Transformations
A lightweight package to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. It is also the data wrangling backend for packages in 'easystats' ecosystem. References: Patil et al. (2022) <doi:10.21105/joss.04684>.
Maintained by Etienne Bacher. Last updated 9 days ago.
datadplyrhacktoberfestjanitormanipulationreshapetidyrwrangling
6.8 match 222 stars 14.71 score 436 scripts 119 dependentseasystats
insight:Easy Access to Model Information for Various Model Objects
A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Maintained by Daniel Lüdecke. Last updated 5 days ago.
easystatshacktoberfestinsightmodelsnamespredictorsrandom
5.8 match 412 stars 17.24 score 568 scripts 210 dependentsdewittpe
qwraps2:Quick Wraps 2
A collection of (wrapper) functions the creator found useful for quickly placing data summaries and formatted regression results into '.Rnw' or '.Rmd' files. Functions for generating commonly used graphics, such as receiver operating curves or Bland-Altman plots, are also provided by 'qwraps2'. 'qwraps2' is a updated version of a package 'qwraps'. The original version 'qwraps' was never submitted to CRAN but can be found at <https://github.com/dewittpe/qwraps/>. The implementation and limited scope of the functions within 'qwraps2' <https://github.com/dewittpe/qwraps2/> is fundamentally different from 'qwraps'.
Maintained by Peter DeWitt. Last updated 5 months ago.
10.1 match 37 stars 9.80 score 448 scriptschjackson
flexsurv:Flexible Parametric Survival and Multi-State Models
Flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models, based on either cause-specific hazards or mixture models.
Maintained by Christopher Jackson. Last updated 2 months ago.
7.3 match 57 stars 13.31 score 632 scripts 43 dependentsmini-pw
SerolyzeR:Reading, Quality Control and Preprocessing of MBA (Multiplex Bead Assay) Data
Speeds up the process of loading raw data from MBA (Multiplex Bead Assay) examinations, performs quality control checks, and automatically normalises the data, preparing it for more advanced, downstream tasks. The main objective of the package is to create a simple environment for a user, who does not necessarily have experience with R language. The package is developed within the project 'PvSTATEM', which is an international project aiming for malaria elimination.
Maintained by Tymoteusz Kwiecinski. Last updated 16 days ago.
14.3 match 4 stars 6.68 scoremini-pw
PvSTATEM:Reading, Quality Control and Preprocessing of MBA (Multiplex Bead Assay) Data
Speeds up the process of loading raw data from MBA (Multiplex Bead Assay) examinations, performs quality control checks, and automatically normalises the data, preparing it for more advanced, downstream tasks. The main objective of the package is to create a simple environment for a user, who does not necessarily have experience with R language. The package is developed within the project of the same name - 'PvSTATEM', which is an international project aiming for malaria elimination.
Maintained by Tymoteusz Kwiecinski. Last updated 17 days ago.
14.3 match 3 stars 6.56 score 7 scriptsmyaseen208
PSLM2015:Pakistan Social and Living Standards Measurement Survey 2014-15
Data and statistics of Pakistan Social and Living Standards Measurement (PSLM) survey 2014-15 from Pakistan Bureau of Statistics (<http://www.pbs.gov.pk/>).
Maintained by Muhammad Yaseen. Last updated 7 years ago.
29.9 match 3.10 score 25 scriptsarvsjo
stdReg:Regression Standardization
Contains functionality for regression standardization. Four general classes of models are allowed; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models and shared frailty gamma-Weibull models. Sjolander, A. (2016) <doi:10.1007/s10654-016-0157-3>.
Maintained by Arvid Sjolander. Last updated 4 years ago.
32.9 match 2.80 score 53 scripts 1 dependentsdaroczig
logger:A Lightweight, Modern and Flexible Logging Utility
Inspired by the the 'futile.logger' R package and 'logging' Python module, this utility provides a flexible and extensible way of formatting and delivering log messages with low overhead.
Maintained by Gergely Daróczi. Last updated 2 months ago.
5.4 match 298 stars 16.88 score 1.5k scripts 98 dependentskaz-yos
tableone:Create 'Table 1' to Describe Baseline Characteristics with or without Propensity Score Weights
Creates 'Table 1', i.e., description of baseline patient characteristics, which is essential in every medical research. Supports both continuous and categorical variables, as well as p-values and standardized mean differences. Weighted data are supported via the 'survey' package.
Maintained by Kazuki Yoshida. Last updated 3 years ago.
baseline-characteristicsdescriptive-statisticsstatistics
6.7 match 221 stars 13.55 score 2.3k scripts 12 dependentsconnordonegan
surveil:Time Series Models for Disease Surveillance
Fits time trend models for routine disease surveillance tasks and returns probability distributions for a variety of quantities of interest, including age-standardized rates, period and cumulative percent change, and measures of health inequality. The models are appropriate for count data such as disease incidence and mortality data, employing a Poisson or binomial likelihood and the first-difference (random-walk) prior for unknown risk. Optionally add a covariance matrix for multiple, correlated time series models. Inference is completed using Markov chain Monte Carlo via the Stan modeling language. References: Donegan, Hughes, and Lee (2022) <doi:10.2196/34589>; Stan Development Team (2021) <https://mc-stan.org>; Theil (1972, ISBN:0-444-10378-3).
Maintained by Connor Donegan. Last updated 8 months ago.
bayesian-statisticscancerhealth-equitypublic-healthrstancpp
18.0 match 2 stars 4.98 score 12 scriptsropensci
EML:Read and Write Ecological Metadata Language Files
Work with Ecological Metadata Language ('EML') files. 'EML' is a widely used metadata standard in the ecological and environmental sciences, described in Jones et al. (2006), <doi:10.1146/annurev.ecolsys.37.091305.110031>.
Maintained by Carl Boettiger. Last updated 3 years ago.
emleml-metadatametadata-standard
8.0 match 97 stars 11.19 score 378 scripts 7 dependentscran
lm.beta:Add Standardized Regression Coefficients to Linear-Model-Objects
Adds standardized regression coefficients to objects created by 'lm'. Also extends the S3 methods 'print', 'summary' and 'coef' with additional boolean argument 'standardized' and provides 'xtable'-support.
Maintained by Stefan Behrendt. Last updated 2 years ago.
14.1 match 6.31 score 612 scripts 6 dependentsips-lmu
emuR:Main Package of the EMU Speech Database Management System
Provide the EMU Speech Database Management System (EMU-SDMS) with database management, data extraction, data preparation and data visualization facilities. See <https://ips-lmu.github.io/The-EMU-SDMS-Manual/> for more details.
Maintained by Markus Jochim. Last updated 1 years ago.
12.8 match 24 stars 6.89 score 135 scripts 1 dependentsbioc
puma:Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)
Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.
Maintained by Xuejun Liu. Last updated 5 months ago.
microarrayonechannelpreprocessingdifferentialexpressionclusteringexonarraygeneexpressionmrnamicroarraychiponchipalternativesplicingdifferentialsplicingbayesiantwochanneldataimporthta2.0
18.8 match 4.53 score 17 scriptsngreifer
WeightIt:Weighting for Covariate Balance in Observational Studies
Generates balancing weights for causal effect estimation in observational studies with binary, multi-category, or continuous point or longitudinal treatments by easing and extending the functionality of several R packages and providing in-house estimation methods. Available methods include those that rely on parametric modeling, optimization, and machine learning. Also allows for assessment of weights and checking of covariate balance by interfacing directly with the 'cobalt' package. Methods for estimating weighted regression models that take into account uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how to install any package 'WeightIt' uses, including those that may not be on CRAN.
Maintained by Noah Greifer. Last updated 5 days ago.
causal-inferenceinverse-probability-weightsobservational-studypropensity-scores
7.3 match 112 stars 11.58 score 508 scripts 3 dependentsblue-matter
MSEtool:Management Strategy Evaluation Toolkit
Development, simulation testing, and implementation of management procedures for fisheries (see Carruthers & Hordyk (2018) <doi:10.1111/2041-210X.13081>).
Maintained by Adrian Hordyk. Last updated 26 days ago.
10.7 match 8 stars 7.69 score 163 scripts 3 dependentslmaowisc
WR:Win Ratio Analysis of Composite Time-to-Event Outcomes
Implements various win ratio methodologies for composite endpoints of death and non-fatal events, including the (stratified) proportional win-fractions (PW) regression models (Mao and Wang, 2020 <doi:10.1111/biom.13382>), (stratified) two-sample tests with possibly recurrent nonfatal event, and sample size calculation for standard win ratio test (Mao et al., 2021 <doi:10.1111/biom.13501>).
Maintained by Lu Mao. Last updated 2 months ago.
13.4 match 6.11 score 43 scriptsrsquaredacademy
olsrr:Tools for Building OLS Regression Models
Tools designed to make it easier for users, particularly beginner/intermediate R users to build ordinary least squares regression models. Includes comprehensive regression output, heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, model fit assessment and variable selection procedures.
Maintained by Aravind Hebbali. Last updated 4 months ago.
collinearity-diagnosticslinear-modelsregressionstepwise-regression
6.7 match 103 stars 12.19 score 1.4k scripts 4 dependentsparklab
Nozzle.R1:Nozzle Reports
The Nozzle package provides an API to generate HTML reports with dynamic user interface elements based on JavaScript and CSS (Cascading Style Sheets). Nozzle was designed to facilitate summarization and rapid browsing of complex results in data analysis pipelines where multiple analyses are performed frequently on big data sets. The package can be applied to any project where user-friendly reports need to be created.
Maintained by Nils Gehlenborg. Last updated 10 years ago.
gehlenborglabhtml-reportreproducible-research
15.3 match 68 stars 5.31 score 10 scripts 2 dependentsnutriverse
zscorer:Child Anthropometry z-Score Calculator
A tool for calculating z-scores and centiles for weight-for-age, length/height-for-age, weight-for-length/height, BMI-for-age, head circumference-for-age, age circumference-for-age, subscapular skinfold-for-age, triceps skinfold-for-age based on the WHO Child Growth Standards.
Maintained by Ernest Guevarra. Last updated 4 years ago.
anthropometric-indicesanthropometrygrowth-chartsgrowth-standardsheight-for-agenutritionweight-for-ageweight-for-heightz-score
11.0 match 14 stars 7.30 score 47 scripts 1 dependentsalexiosg
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.
6.6 match 26 stars 12.13 score 1.3k scripts 15 dependentsstatist7
sitar:Super Imposition by Translation and Rotation Growth Curve Analysis
Functions for fitting and plotting SITAR (Super Imposition by Translation And Rotation) growth curve models. SITAR is a shape-invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales. The model was first described by Lindstrom (1995) <doi:10.1002/sim.4780141807> and developed as the SITAR method by Cole et al (2010) <doi:10.1093/ije/dyq115>.
Maintained by Tim Cole. Last updated 2 months ago.
9.2 match 13 stars 8.69 score 58 scripts 3 dependentstidymodels
hardhat:Construct Modeling Packages
Building modeling packages is hard. A large amount of effort generally goes into providing an implementation for a new method that is efficient, fast, and correct, but often less emphasis is put on the user interface. A good interface requires specialized knowledge about S3 methods and formulas, which the average package developer might not have. The goal of 'hardhat' is to reduce the burden around building new modeling packages by providing functionality for preprocessing, predicting, and validating input.
Maintained by Hannah Frick. Last updated 1 months ago.
5.3 match 103 stars 14.88 score 175 scripts 436 dependentswjschne
simstandard:Generate Standardized Data
Creates simulated data from structural equation models with standardized loading. Data generation methods are described in Schneider (2013) <doi:10.1177/0734282913478046>.
Maintained by W. Joel Schneider. Last updated 11 months ago.
12.8 match 6 stars 6.07 score 66 scripts 2 dependentsjeksterslab
cTMed:Continuous Time Mediation
Calculates standard errors and confidence intervals for effects in continuous-time mediation models. This package extends the work of Deboeck and Preacher (2015) <doi:10.1080/10705511.2014.973960> and Ryan and Hamaker (2021) <doi:10.1007/s11336-021-09767-0> by providing methods to generate standard errors and confidence intervals for the total, direct, and indirect effects in these models.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 20 days ago.
centralitycontinuous-timedelta-methodmediationmonte-carlo-methodnetworkopenblascppopenmp
17.0 match 4.56 score 24 scriptsbpfaff
QRM:Provides R-Language Code to Examine Quantitative Risk Management Concepts
Provides functions/methods to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Ruediger Frey, and Paul Embrechts.
Maintained by Bernhard Pfaff. Last updated 5 years ago.
16.9 match 4.53 score 181 scripts 5 dependentsum-kevinhe
pprof:Modeling, Standardization and Testing for Provider Profiling
Implements linear and generalized linear models for provider profiling, incorporating both fixed and random effects. For large-scale providers, the linear profiled-based method and the SerBIN method for binary data reduce the computational burden. Provides post-modeling features, such as indirect and direct standardization measures, hypothesis testing, confidence intervals, and post-estimation visualization. For more information, see Wu et al. (2022) <doi:10.1002/sim.9387>.
Maintained by Xiaohan Liu. Last updated 5 days ago.
18.7 match 4.08 score 3 scriptsrvlenth
emmeans:Estimated Marginal Means, aka Least-Squares Means
Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Maintained by Russell V. Lenth. Last updated 3 days ago.
4.0 match 377 stars 19.19 score 13k scripts 187 dependentsajrgodfrey
BrailleR:Improved Access for Blind Users
Blind users do not have access to the graphical output from R without printing the content of graphics windows to an embosser of some kind. This is not as immediate as is required for efficient access to statistical output. The functions here are created so that blind people can make even better use of R. This includes the text descriptions of graphs, convenience functions to replace the functionality offered in many GUI front ends, and experimental functionality for optimising graphical content to prepare it for embossing as tactile images.
Maintained by A. Jonathan R. Godfrey. Last updated 11 months ago.
8.5 match 123 stars 8.90 score 143 scriptsmwheymans
miceafter:Data and Statistical Analyses after Multiple Imputation
Statistical Analyses and Pooling after Multiple Imputation. A large variety of repeated statistical analysis can be performed and finally pooled. Statistical analysis that are available are, among others, Levene's test, Odds and Risk Ratios, One sample proportions, difference between proportions and linear and logistic regression models. Functions can also be used in combination with the Pipe operator. More and more statistical analyses and pooling functions will be added over time. Heymans (2007) <doi:10.1186/1471-2288-7-33>. Eekhout (2017) <doi:10.1186/s12874-017-0404-7>. Wiel (2009) <doi:10.1093/biostatistics/kxp011>. Marshall (2009) <doi:10.1186/1471-2288-9-57>. Sidi (2021) <doi:10.1080/00031305.2021.1898468>. Lott (2018) <doi:10.1080/00031305.2018.1473796>. Grund (2021) <doi:10.31234/osf.io/d459g>.
Maintained by Martijn Heymans. Last updated 2 years ago.
15.3 match 2 stars 4.84 score 23 scriptseblondel
rsdmx:Tools for Reading SDMX Data and Metadata
Set of classes and methods to read data and metadata documents exchanged through the Statistical Data and Metadata Exchange (SDMX) framework, currently focusing on the SDMX XML standard format (SDMX-ML).
Maintained by Emmanuel Blondel. Last updated 17 days ago.
apidatastructuresdsdreadreadsdmxsdmxsdmx-formatsdmx-providersdmx-standardsstatisticstimeseriesweb-services
8.0 match 105 stars 9.22 score 4 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.
3.7 match 419 stars 19.88 score 88k scripts 7.9k dependentsbioc
DESeq2:Differential gene expression analysis based on the negative binomial distribution
Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.
Maintained by Michael Love. Last updated 11 days ago.
sequencingrnaseqchipseqgeneexpressiontranscriptionnormalizationdifferentialexpressionbayesianregressionprincipalcomponentclusteringimmunooncologyopenblascpp
4.6 match 375 stars 16.11 score 17k scripts 115 dependentsmicrosoft
wpa:Tools for Analysing and Visualising Viva Insights Data
Opinionated functions that enable easier and faster analysis of Viva Insights data. There are three main types of functions in 'wpa': (i) Standard functions create a 'ggplot' visual or a summary table based on a specific Viva Insights metric; (2) Report Generation functions generate HTML reports on a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover more specific applications (e.g. Subject Line text mining) of Viva Insights data. This package adheres to 'tidyverse' principles and works well with the pipe syntax. 'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for simplicity.
Maintained by Martin Chan. Last updated 4 months ago.
11.0 match 30 stars 6.69 score 39 scripts 1 dependentslme4
lme4:Linear Mixed-Effects Models using 'Eigen' and S4
Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Maintained by Ben Bolker. Last updated 3 days ago.
3.5 match 647 stars 20.69 score 35k scripts 1.5k dependentsstmcg
estmeansd:Estimating the Sample Mean and Standard Deviation from Commonly Reported Quantiles in Meta-Analysis
Implements the methods of McGrath et al. (2020) <doi:10.1177/0962280219889080> and Cai et al. (2021) <doi:10.1177/09622802211047348> for estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. These methods can be applied to studies that report the sample median, sample size, and one or both of (i) the sample minimum and maximum values and (ii) the first and third quartiles. The corresponding standard error estimators described by McGrath et al. (2023) <doi:10.1177/09622802221139233> are also included.
Maintained by Sean McGrath. Last updated 1 years ago.
15.3 match 2 stars 4.70 score 58 scripts 2 dependentssafetygraphics
safetyGraphics:Interactive Graphics for Monitoring Clinical Trial Safety
A framework for evaluation of clinical trial safety. Users can interactively explore their data using the included 'Shiny' application.
Maintained by Jeremy Wildfire. Last updated 2 years ago.
8.8 match 98 stars 8.18 score 111 scriptsplangfelder
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.
7.3 match 54 stars 9.65 score 5.3k scripts 32 dependentsdanlwarren
ENMTools:Analysis of Niche Evolution using Niche and Distribution Models
Constructing niche models and analyzing patterns of niche evolution. Acts as an interface for many popular modeling algorithms, and allows users to conduct Monte Carlo tests to address basic questions in evolutionary ecology and biogeography. Warren, D.L., R.E. Glor, and M. Turelli (2008) <doi:10.1111/j.1558-5646.2008.00482.x> Glor, R.E., and D.L. Warren (2011) <doi:10.1111/j.1558-5646.2010.01177.x> Warren, D.L., R.E. Glor, and M. Turelli (2010) <doi:10.1111/j.1600-0587.2009.06142.x> Cardillo, M., and D.L. Warren (2016) <doi:10.1111/geb.12455> D.L. Warren, L.J. Beaumont, R. Dinnage, and J.B. Baumgartner (2019) <doi:10.1111/ecog.03900>.
Maintained by Dan Warren. Last updated 2 months ago.
10.1 match 105 stars 6.91 score 126 scriptsbenmbutler
powdR:Full Pattern Summation of X-Ray Powder Diffraction Data
Full pattern summation of X-ray powder diffraction data as described in Chipera and Bish (2002) <doi:10.1107/S0021889802017405> and Butler and Hillier (2021) <doi:10.1016/j.cageo.2020.104662>. Derives quantitative estimates of crystalline and amorphous phase concentrations in complex mixtures.
Maintained by Benjamin Butler. Last updated 3 years ago.
12.6 match 12 stars 5.56 score 30 scriptseitsupi
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 1 days ago.
14.3 match 40 stars 4.86 score 1 scriptsksawicka
spup:Spatial Uncertainty Propagation Analysis
Uncertainty propagation analysis in spatial environmental modelling following methodology described in Heuvelink et al. (2007) <doi:10.1080/13658810601063951> and Brown and Heuvelink (2007) <doi:10.1016/j.cageo.2006.06.015>. The package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model outputs. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is accommodated for. The MC realizations may be used as input to the environmental models called from R, or externally.
Maintained by Kasia Sawicka. Last updated 1 years ago.
monte-carlospatialuncertainty-analysisuncertainty-propagation
10.9 match 9 stars 6.31 score 57 scriptsdynverse
dyngen:A Multi-Modal Simulator for Spearheading Single-Cell Omics Analyses
A novel, multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. 'dyngen' is more flexible than current single-cell simulation engines. It allows better method development and benchmarking, thereby stimulating development and testing of novel computational methods. Cannoodt et al. (2021) <doi:10.1038/s41467-021-24152-2>.
Maintained by Robrecht Cannoodt. Last updated 2 years ago.
benchmarkingsingle-cellsingle-cell-analysissingle-cell-omics
9.1 match 74 stars 7.53 score 57 scriptstobiaskley
quantspec:Quantile-Based Spectral Analysis of Time Series
Methods to determine, smooth and plot quantile periodograms for univariate and multivariate time series.
Maintained by Tobias Kley. Last updated 9 years ago.
11.7 match 10 stars 5.84 score 46 scripts 1 dependentsaphalo
photobiology:Photobiological Calculations
Definitions of classes, methods, operators and functions for use in photobiology and radiation meteorology and climatology. Calculation of effective (weighted) and not-weighted irradiances/doses, fluence rates, transmittance, reflectance, absorptance, absorbance and diverse ratios and other derived quantities from spectral data. Local maxima and minima: peaks, valleys and spikes. Conversion between energy-and photon-based units. Wavelength interpolation. Astronomical calculations related solar angles and day length. Colours and vision. This package is part of the 'r4photobiology' suite, Aphalo, P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Maintained by Pedro J. Aphalo. Last updated 3 days ago.
lightphotobiologyquantificationr4photobiology-suiteradiationspectrasun-position
7.3 match 4 stars 9.35 score 604 scripts 12 dependentssebkrantz
collapse:Advanced and Fast Data Transformation
A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It is well integrated with base R classes, 'dplyr'/'tibble', 'data.table', 'sf', 'units', 'plm' (panel-series and data frames), and 'xts'/'zoo'.
Maintained by Sebastian Krantz. Last updated 6 days ago.
data-aggregationdata-analysisdata-manipulationdata-processingdata-sciencedata-transformationeconometricshigh-performancepanel-datascientific-computingstatisticstime-seriesweightedweightscppopenmp
4.1 match 672 stars 16.63 score 708 scripts 97 dependentsstla
syt:Young Tableaux
Deals with Young tableaux (field of combinatorics). For standard Young tabeaux, performs enumeration, counting, random generation, the Robinson-Schensted correspondence, and conversion to and from paths on the Young lattice. Also performs enumeration and counting of semistandard Young tableaux, enumeration of skew semistandard Young tableaux, enumeration of Gelfand-Tsetlin patterns, and computation of Kostka numbers.
Maintained by Stéphane Laurent. Last updated 8 months ago.
13.5 match 3 stars 5.03 score 24 scripts 1 dependentscliffordlai
bestglm:Best Subset GLM and Regression Utilities
Best subset glm using information criteria or cross-validation, carried by using 'leaps' algorithm (Furnival and Wilson, 1974) <doi:10.2307/1267601> or complete enumeration (Morgan and Tatar, 1972) <doi:10.1080/00401706.1972.10488918>. Implements PCR and PLS using AIC/BIC. Implements one-standard deviation rule for use with the 'caret' package.
Maintained by Yuanhao Lai. Last updated 5 years ago.
12.8 match 5.29 score 418 scripts 5 dependentstimriffe
HMDHFDplus:Read Human Mortality Database and Human Fertility Database Data from the Web
Utilities for reading data from the Human Mortality Database (<https://www.mortality.org>), Human Fertility Database (<https://www.humanfertility.org>), and similar databases from the web or locally into an R session as data.frame objects. These are the two most widely used sources of demographic data to study basic demographic change, trends, and develop new demographic methods. Other supported databases at this time include the Human Fertility Collection (<https://www.fertilitydata.org>), The Japanese Mortality Database (<https://www.ipss.go.jp/p-toukei/JMD/index-en.html>), and the Canadian Human Mortality Database (<http://www.bdlc.umontreal.ca/chmd/>). Arguments and data are standardized.
Maintained by Tim Riffe. Last updated 1 months ago.
10.5 match 2 stars 6.48 score 217 scripts 10 dependentsr-gregmisc
gdata:Various R Programming Tools for Data Manipulation
Various R programming tools for data manipulation, including medical unit conversions, combining objects, character vector operations, factor manipulation, obtaining information about R objects, generating fixed-width format files, extracting components of date & time objects, operations on columns of data frames, matrix operations, operations on vectors, operations on data frames, value of last evaluated expression, and a resample() wrapper for sample() that ensures consistent behavior for both scalar and vector arguments.
Maintained by Arni Magnusson. Last updated 2 months ago.
4.9 match 9 stars 13.62 score 4.5k scripts 124 dependentsbioc
gDRutils:A package with helper functions for processing drug response data
This package contains utility functions used throughout the gDR platform to fit data, manipulate data, and convert and validate data structures. This package also has the necessary default constants for gDR platform. Many of the functions are utilized by the gDRcore package.
Maintained by Arkadiusz Gladki. Last updated 4 days ago.
9.0 match 2 stars 7.40 score 3 scripts 3 dependentsewenharrison
finalfit:Quickly Create Elegant Regression Results Tables and Plots when Modelling
Generate regression results tables and plots in final format for publication. Explore models and export directly to PDF and 'Word' using 'RMarkdown'.
Maintained by Ewen Harrison. Last updated 7 months ago.
5.8 match 270 stars 11.43 score 1.0k scriptsinsightsengineering
teal.modules.clinical:'teal' Modules for Standard Clinical Outputs
Provides user-friendly tools for creating and customizing clinical trial reports. By leveraging the 'teal' framework, this package provides 'teal' modules to easily create an interactive panel that allows for seamless adjustments to data presentation, thereby streamlining the creation of detailed and accurate reports.
Maintained by Dawid Kaledkowski. Last updated 16 days ago.
clinical-trialsmodulesnestoutputsshiny
6.5 match 34 stars 10.25 score 149 scriptselipousson
sfext:Extra Functions for Simple Feature Data
Extra functions with additional options for reading, writing, and transforming spatial data. Includes a variety of utility functions for working with tabular data with coordinates and distance and area units.
Maintained by Eli Pousson. Last updated 4 months ago.
10.9 match 20 stars 6.03 score 24 scripts 5 dependentscran
fBasics:Rmetrics - Markets and Basic Statistics
Provides a collection of functions to explore and to investigate basic properties of financial returns and related quantities. The covered fields include techniques of explorative data analysis and the investigation of distributional properties, including parameter estimation and hypothesis testing. Even more there are several utility functions for data handling and management.
Maintained by Georgi N. Boshnakov. Last updated 7 months ago.
9.2 match 2 stars 7.11 score 129 dependentsjinkim3
kim:A Toolkit for Behavioral Scientists
A collection of functions for analyzing data typically collected or used by behavioral scientists. Examples of the functions include a function that compares groups in a factorial experimental design, a function that conducts two-way analysis of variance (ANOVA), and a function that cleans a data set generated by Qualtrics surveys. Some of the functions will require installing additional package(s). Such packages and other references are cited within the section describing the relevant functions. Many functions in this package rely heavily on these two popular R packages: Dowle et al. (2021) <https://CRAN.R-project.org/package=data.table>. Wickham et al. (2021) <https://CRAN.R-project.org/package=ggplot2>.
Maintained by Jin Kim. Last updated 19 days ago.
14.0 match 7 stars 4.66 score 3 scriptscardiomoon
interpretCI:Estimate the Confidence Interval and Interpret Step by Step
Estimate confidence intervals for mean, proportion, mean difference for unpaired and paired samples and proportion difference. Plot the confidence intervals. Generate documents explaining the statistical result step by step.
Maintained by Keon-Woong Moon. Last updated 3 years ago.
10.8 match 4 stars 6.03 score 49 scriptsskembel
picante:Integrating Phylogenies and Ecology
Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) <doi:10.1093/bioinformatics/btq166>.
Maintained by Steven W. Kembel. Last updated 2 years ago.
5.6 match 34 stars 11.42 score 1.1k scripts 16 dependentshenrikbengtsson
matrixStats:Functions that Apply to Rows and Columns of Matrices (and to Vectors)
High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().
Maintained by Henrik Bengtsson. Last updated 2 months ago.
3.5 match 208 stars 18.09 score 20k scripts 2.3k dependentsbioc
Biostrings:Efficient manipulation of biological strings
Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences.
Maintained by Hervé Pagès. Last updated 24 days ago.
sequencematchingalignmentsequencinggeneticsdataimportdatarepresentationinfrastructurebioconductor-packagecore-package
3.6 match 61 stars 17.83 score 8.6k scripts 1.2k dependentsopenanalytics
inTextSummaryTable:Creation of in-Text Summary Table
Creation of tables of summary statistics or counts for clinical data (for 'TLFs'). These tables can be exported as in-text table (with the 'flextable' package) for a Clinical Study Report (Word format) or a 'topline' presentation (PowerPoint format), or as interactive table (with the 'DT' package) to an html document for clinical data review.
Maintained by Laure Cougnaud. Last updated 9 months ago.
11.4 match 1 stars 5.52 score 47 scriptsngreifer
cobalt:Covariate Balance Tables and Plots
Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'WeightIt', 'MatchThem', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', 'cem', 'sbw', and 'designmatch' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets or data sets with multi-category, continuous, or longitudinal treatments.
Maintained by Noah Greifer. Last updated 11 months ago.
causal-inferencepropensity-scores
4.8 match 75 stars 12.98 score 1.0k scripts 8 dependentshredestig
crmn:CCMN and Other Normalization Methods for Metabolomics Data
Implements the Cross-contribution Compensating Multiple standard Normalization (CCMN) method described in Redestig et al. (2009) Analytical Chemistry https://doi.org/10.1021/ac901143w and other normalization algorithms.
Maintained by Henning Redestig. Last updated 5 years ago.
13.8 match 1 stars 4.56 score 24 scripts 1 dependentsropensci
datefixR:Standardize Dates in Different Formats or with Missing Data
There are many different formats dates are commonly represented with: the order of day, month, or year can differ, different separators ("-", "/", or whitespace) can be used, months can be numerical, names, or abbreviations and year given as two digits or four. 'datefixR' takes dates in all these different formats and converts them to R's built-in date class. If 'datefixR' cannot standardize a date, such as because it is too malformed, then the user is told which date cannot be standardized and the corresponding ID for the row. 'datefixR' also allows the imputation of missing days and months with user-controlled behavior.
Maintained by Nathan Constantine-Cooke. Last updated 3 months ago.
8.6 match 34 stars 7.24 score 16 scriptsbioc
spiky:Spike-in calibration for cell-free MeDIP
spiky implements methods and model generation for cfMeDIP (cell-free methylated DNA immunoprecipitation) with spike-in controls. CfMeDIP is an enrichment protocol which avoids destructive conversion of scarce template, making it ideal as a "liquid biopsy," but creating certain challenges in comparing results across specimens, subjects, and experiments. The use of synthetic spike-in standard oligos allows diagnostics performed with cfMeDIP to quantitatively compare samples across subjects, experiments, and time points in both relative and absolute terms.
Maintained by Tim Triche. Last updated 5 months ago.
differentialmethylationdnamethylationnormalizationpreprocessingqualitycontrolsequencing
12.7 match 2 stars 4.90 score 3 scriptsflr
FLa4a:A Simple and Robust Statistical Catch at Age Model
A simple and robust statistical Catch at Age model that is specifically designed for stocks with intermediate levels of data quantity and quality.
Maintained by Ernesto Jardim. Last updated 5 days ago.
9.3 match 12 stars 6.66 score 177 scripts 2 dependentsdkaschek
dMod:Dynamic Modeling and Parameter Estimation in ODE Models
The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.
Maintained by Daniel Kaschek. Last updated 10 days ago.
7.4 match 20 stars 8.35 score 251 scriptsflorianhartig
DHARMa:Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB', 'GLMMadaptive', and 'spaMM'; phylogenetic linear models from 'phylolm' (classes 'phylolm' and 'phyloglm'); generalized additive models ('gam' from 'mgcv'); 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial, phylogenetic and temporal autocorrelation.
Maintained by Florian Hartig. Last updated 12 days ago.
glmmregressionregression-diagnosticsresidual
4.2 match 226 stars 14.74 score 2.8k scripts 10 dependentsggobi
GGally:Extension to 'ggplot2'
The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.
Maintained by Barret Schloerke. Last updated 10 months ago.
3.8 match 597 stars 16.15 score 17k scripts 154 dependentsworldhealthorganization
anthro:Computation of the WHO Child Growth Standards
Provides WHO Child Growth Standards (z-scores) with confidence intervals and standard errors around the prevalence estimates, taking into account complex sample designs. More information on the methods is available online: <https://www.who.int/tools/child-growth-standards>.
Maintained by Dirk Schumacher. Last updated 5 months ago.
9.7 match 32 stars 6.30 score 26 scripts 2 dependentsmahshaaban
pcr:Analyzing Real-Time Quantitative PCR Data
Calculates the amplification efficiency and curves from real-time quantitative PCR (Polymerase Chain Reaction) data. Estimates the relative expression from PCR data using the double delta CT and the standard curve methods Livak & Schmittgen (2001) <doi:10.1006/meth.2001.1262>. Tests for statistical significance using two-group tests and linear regression Yuan et al. (2006) <doi: 10.1186/1471-2105-7-85>.
Maintained by Mahmoud Ahmed. Last updated 8 months ago.
data-analysesmolecular-biologyqpcr
8.4 match 28 stars 7.25 score 63 scriptsulrichriegel
Pareto:The Pareto, Piecewise Pareto and Generalized Pareto Distribution
Utilities for the Pareto, piecewise Pareto and generalized Pareto distribution that are useful for reinsurance pricing. In particular, the package provides a non-trivial algorithm that can be used to match the expected losses of a tower of reinsurance layers with a layer-independent collective risk model. The theoretical background of the matching algorithm and most other methods are described in Ulrich Riegel (2018) <doi:10.1007/s13385-018-0177-3>.
Maintained by Ulrich Riegel. Last updated 2 years ago.
8.6 match 10 stars 7.00 score 134 scripts 1 dependentscran
Monte.Carlo.se:Monte Carlo Standard Errors
Computes Monte Carlo standard errors for summaries of Monte Carlo output. Summaries and their standard errors are based on columns of Monte Carlo simulation output. Dennis D. Boos and Jason A. Osborne (2015) <doi:10.1111/insr.12087>.
Maintained by Dennis Boos. Last updated 2 years ago.
23.1 match 2.60 scoreielbadisy
mcstatsim:Monte Carlo Statistical Simulation Tools Using a Functional Approach
A lightweight package designed to facilitate statistical simulations through functional programming. It centralizes the simulation process into a single higher-order function, enhancing manageability and usability without adding overhead from external dependencies. The package includes ready-to-use functions for common simulation targets. A detailed example can be found on <https://github.com/ielbadisy/mcstatsim>.
Maintained by Imad EL BADISY. Last updated 7 months ago.
16.9 match 1 stars 3.54 score 7 scriptsbioc
sparseMatrixStats:Summary Statistics for Rows and Columns of Sparse Matrices
High performance functions for row and column operations on sparse matrices. For example: col / rowMeans2, col / rowMedians, col / rowVars etc. Currently, the optimizations are limited to data in the column sparse format. This package is inspired by the matrixStats package by Henrik Bengtsson.
Maintained by Constantin Ahlmann-Eltze. Last updated 5 months ago.
infrastructuresoftwaredatarepresentationcpp
5.0 match 54 stars 11.98 score 174 scripts 126 dependentsneuropsychology
psycho:Efficient and Publishing-Oriented Workflow for Psychological Science
The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.
Maintained by Dominique Makowski. Last updated 4 years ago.
apaapa6bayesiancorrelationformatinterpretationmixed-modelsneurosciencepsychopsychologyrstanarmstatistics
5.5 match 149 stars 10.86 score 628 scripts 5 dependentsopenvolley
datavolley:Reading and Analyzing DataVolley Scout Files
Provides functions for parsing and working with volleyball match files in DataVolley format.
Maintained by Ben Raymond. Last updated 2 months ago.
openvolleysports-analyticsvolleyball
7.1 match 31 stars 8.31 score 94 scripts 11 dependentssfcheung
semfindr:Influential Cases in Structural Equation Modeling
Sensitivity analysis in structural equation modeling using influence measures and diagnostic plots. Support leave-one-out casewise sensitivity analysis presented by Pek and MacCallum (2011) <doi:10.1080/00273171.2011.561068> and approximate casewise influence using scores and casewise likelihood.
Maintained by Shu Fai Cheung. Last updated 13 days ago.
diagnosticsinfluential-caseslavaanoutlier-detectionsensitivity-analysisstructural-equation-modeling
9.8 match 1 stars 6.03 score 90 scriptsmotherhack3r
mitre:Cybersecurity MITRE Standards Data and Digraphs
Extract, transform and load MITRE standards. This package gives you an approach to cybersecurity data sets. All data sets are build on runtime downloading raw data from MITRE public services. MITRE <https://www.mitre.org/> is a government-funded research organization based in Bedford and McLean. Current version includes most used standards as data frames. It also provide a list of nodes and edges with all relationships.
Maintained by Humbert Costas. Last updated 4 years ago.
data-driven-securitymitremitre-shield
11.9 match 19 stars 4.98 score 6 scriptspauljohn32
rockchalk:Regression Estimation and Presentation
A collection of functions for interpretation and presentation of regression analysis. These functions are used to produce the statistics lectures in <https://pj.freefaculty.org/guides/>. Includes regression diagnostics, regression tables, and plots of interactions and "moderator" variables. The emphasis is on "mean-centered" and "residual-centered" predictors. The vignette 'rockchalk' offers a fairly comprehensive overview. The vignette 'Rstyle' has advice about coding in R. The package title 'rockchalk' refers to our school motto, 'Rock Chalk Jayhawk, Go K.U.'.
Maintained by Paul E. Johnson. Last updated 3 years ago.
8.3 match 7.13 score 584 scripts 18 dependentscran
MASS:Support Functions and Datasets for Venables and Ripley's MASS
Functions and datasets to support Venables and Ripley, "Modern Applied Statistics with S" (4th edition, 2002).
Maintained by Brian Ripley. Last updated 16 days ago.
5.5 match 19 stars 10.53 score 11k dependentsfinnishcancerregistry
popEpi:Functions for Epidemiological Analysis using Population Data
Enables computation of epidemiological statistics, including those where counts or mortality rates of the reference population are used. Currently supported: excess hazard models (Dickman, Sloggett, Hills, and Hakulinen (2012) <doi:10.1002/sim.1597>), rates, mean survival times, relative/net survival (in particular the Ederer II (Ederer and Heise (1959)) and Pohar Perme (Pohar Perme, Stare, and Esteve (2012) <doi:10.1111/j.1541-0420.2011.01640.x>) estimators), and standardized incidence and mortality ratios, all of which can be easily adjusted for by covariates such as age. Fast splitting and aggregation of 'Lexis' objects (from package 'Epi') and other computations achieved using 'data.table'.
Maintained by Joonas Miettinen. Last updated 1 months ago.
adjust-estimatesage-adjustingdirect-adjustingepidemiologyindirect-adjustingsurvival
7.3 match 8 stars 8.05 score 117 scripts 1 dependentsmuschellij2
fslr:Wrapper Functions for 'FSL' ('FMRIB' Software Library) from Functional MRI of the Brain ('FMRIB')
Wrapper functions that interface with 'FSL' <http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>, a powerful and commonly-used 'neuroimaging' software, using system commands. The goal is to be able to interface with 'FSL' completely in R, where you pass R objects of class 'nifti', implemented by package 'oro.nifti', and the function executes an 'FSL' command and returns an R object of class 'nifti' if desired.
Maintained by John Muschelli. Last updated 1 months ago.
fslfslrneuroimagingneuroimaging-analysisneuroimaging-data-science
7.3 match 41 stars 8.01 score 420 scriptsbioc
MatrixGenerics:S4 Generic Summary Statistic Functions that Operate on Matrix-Like Objects
S4 generic functions modeled after the 'matrixStats' API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. Other package developers can import this package and handle a different matrix implementations without worrying about incompatibilities.
Maintained by Peter Hickey. Last updated 2 months ago.
infrastructuresoftwarebioconductor-packagecore-package
5.0 match 12 stars 11.64 score 129 scripts 1.3k dependentssbegueria
SPEI:Calculation of the Standardized Precipitation-Evapotranspiration Index
A set of functions for computing potential evapotranspiration and several widely used drought indices including the Standardized Precipitation-Evapotranspiration Index (SPEI).
Maintained by Santiago Beguería. Last updated 2 years ago.
6.2 match 82 stars 9.27 score 314 scripts 20 dependentsopenanalytics
clinUtils:General Utility Functions for Analysis of Clinical Data
Utility functions to facilitate the import, the reporting and analysis of clinical data. Example datasets in 'SDTM' and 'ADaM' format, containing a subset of patients/domains from the 'CDISC Pilot 01 study' are also available as R datasets to demonstrate the package functionalities.
Maintained by Laure Cougnaud. Last updated 10 months ago.
8.5 match 3 stars 6.78 score 105 scripts 3 dependentsgeanders
weathermetrics:Functions to Convert Between Weather Metrics
Functions to convert between weather metrics, including conversions for metrics of temperature, air moisture, wind speed, and precipitation. This package also includes functions to calculate the heat index from air temperature and air moisture.
Maintained by Brooke Anderson. Last updated 8 years ago.
6.9 match 23 stars 8.32 score 506 scripts 1 dependentskenithgrey
ggQC:Quality Control Charts for 'ggplot'
Plot single and faceted type quality control charts for 'ggplot'.
Maintained by Kenith Grey. Last updated 6 years ago.
8.6 match 46 stars 6.74 score 119 scriptsbioc
MetaboCoreUtils:Core Utils for Metabolomics Data
MetaboCoreUtils defines metabolomics-related core functionality provided as low-level functions to allow a data structure-independent usage across various R packages. This includes functions to calculate between ion (adduct) and compound mass-to-charge ratios and masses or functions to work with chemical formulas. The package provides also a set of adduct definitions and information on some commercially available internal standard mixes commonly used in MS experiments.
Maintained by Johannes Rainer. Last updated 5 months ago.
infrastructuremetabolomicsmassspectrometrymass-spectrometry
6.1 match 9 stars 9.40 score 58 scripts 36 dependentscbailiss
pivottabler:Create Pivot Tables
Create regular pivot tables with just a few lines of R. More complex pivot tables can also be created, e.g. pivot tables with irregular layouts, multiple calculations and/or derived calculations based on multiple data frames. Pivot tables are constructed using R only and can be written to a range of output formats (plain text, 'HTML', 'Latex' and 'Excel'), including with styling/formatting.
Maintained by Christopher Bailiss. Last updated 1 years ago.
calculationshtmlhtmlwidgetlatexpivot-tablesvisualization
7.1 match 122 stars 8.08 score 358 scripts 1 dependentswviechtb
metafor:Meta-Analysis Package for R
A comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit equal-, fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, bubble, and GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted. An introduction to the package can be found in Viechtbauer (2010) <doi:10.18637/jss.v036.i03>.
Maintained by Wolfgang Viechtbauer. Last updated 1 days ago.
meta-analysismixed-effectsmultilevel-modelsmultivariate
3.5 match 246 stars 16.30 score 4.9k scripts 92 dependentsopengeos
whitebox:'WhiteboxTools' R Frontend
An R frontend for the 'WhiteboxTools' library, which is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. 'WhiteboxTools' can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. 'WhiteboxTools' also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. Suggested citation: Lindsay (2016) <doi:10.1016/j.cageo.2016.07.003>.
Maintained by Andrew Brown. Last updated 5 months ago.
geomorphometrygeoprocessinggeospatialgishydrologyremote-sensingrstudio
5.9 match 173 stars 9.65 score 203 scripts 2 dependentsarcaldwell49
Superpower:Simulation-Based Power Analysis for Factorial Designs
Functions to perform simulations of ANOVA designs of up to three factors. Calculates the observed power and average observed effect size for all main effects and interactions in the ANOVA, and all simple comparisons between conditions. Includes functions for analytic power calculations and additional helper functions that compute effect sizes for ANOVA designs, observed error rates in the simulations, and functions to plot power curves. Please see Lakens, D., & Caldwell, A. R. (2021). "Simulation-Based Power Analysis for Factorial Analysis of Variance Designs". <doi:10.1177/2515245920951503>.
Maintained by Aaron Caldwell. Last updated 3 months ago.
6.3 match 66 stars 9.02 score 106 scripts 1 dependentsjinghuazhao
gap:Genetic Analysis Package
As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. <doi:10.18637/jss.v023.i08>], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).
Maintained by Jing Hua Zhao. Last updated 16 days ago.
4.8 match 12 stars 11.88 score 448 scripts 16 dependentssciviews
svDialogs:'SciViews' - Standard Dialog Boxes for Windows, MacOS and Linuxes
Quickly construct standard dialog boxes for your GUI, including message boxes, input boxes, list, file or directory selection, ... In case R cannot display GUI dialog boxes, a simpler command line version of these interactive elements is also provided as fallback solution.
Maintained by Philippe Grosjean. Last updated 3 years ago.
6.4 match 8 stars 8.85 score 289 scripts 12 dependentsmamaz7
AICcmodavg:Model Selection and Multimodel Inference Based on (Q)AIC(c)
Functions to implement model selection and multimodel inference based on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc) from various model object classes. The package implements classic model averaging for a given parameter of interest or predicted values, as well as a shrinkage version of model averaging parameter estimates or effect sizes. The package includes diagnostics and goodness-of-fit statistics for certain model types including those of 'unmarkedFit' classes estimating demographic parameters after accounting for imperfect detection probabilities. Some functions also allow the creation of model selection tables for Bayesian models of the 'bugs', 'rjags', and 'jagsUI' classes. Functions also implement model selection using BIC. Objects following model selection and multimodel inference can be formatted to LaTeX using 'xtable' methods included in the package.
Maintained by Marc J. Mazerolle. Last updated 10 days ago.
7.2 match 1 stars 7.83 score 1.8k scripts 8 dependentsropensci
tracerer:Tracer from R
'BEAST2' (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'Tracer' (<https://github.com/beast-dev/tracer/>) is a GUI tool to parse and analyze the files generated by 'BEAST2'. This package provides a way to parse and analyze 'BEAST2' input files without active user input, but using R function calls instead.
Maintained by Richèl J.C. Bilderbeek. Last updated 1 years ago.
8.7 match 8 stars 6.49 score 86 scripts 3 dependentsnacnudus
tidyxl:Read Untidy Excel Files
Imports non-tabular from Excel files into R. Exposes cell content, position and formatting in a tidy structure for further manipulation. Tokenizes Excel formulas. Supports '.xlsx' and '.xlsm' via the embedded 'RapidXML' C++ library <https://rapidxml.sourceforge.net>. Does not support '.xlsb' or '.xls'.
Maintained by Duncan Garmonsway. Last updated 1 years ago.
excelreaderrcppspreadsheettidycpp
5.3 match 251 stars 10.69 score 382 scripts 13 dependentspharmaverse
admiralophtha:ADaM in R Asset Library - Ophthalmology
Aids the programming of Clinical Data Standards Interchange Consortium (CDISC) compliant Ophthalmology 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/adamig-v1-3-release-package>).
Maintained by Edoardo Mancini. Last updated 2 months ago.
7.0 match 15 stars 7.94 score 10 scriptstidymodels
infer:Tidy Statistical Inference
The objective of this package is to perform inference using an expressive statistical grammar that coheres with the tidy design framework.
Maintained by Simon Couch. Last updated 6 months ago.
3.5 match 734 stars 15.69 score 3.5k scripts 17 dependentsveronica0206
nlpsem:Linear and Nonlinear Longitudinal Process in Structural Equation Modeling Framework
Provides computational tools for nonlinear longitudinal models, in particular the intrinsically nonlinear models, in four scenarios: (1) univariate longitudinal processes with growth factors, with or without covariates including time-invariant covariates (TICs) and time-varying covariates (TVCs); (2) multivariate longitudinal processes that facilitate the assessment of correlation or causation between multiple longitudinal variables; (3) multiple-group models for scenarios (1) and (2) to evaluate differences among manifested groups, and (4) longitudinal mixture models for scenarios (1) and (2), with an assumption that trajectories are from multiple latent classes. The methods implemented are introduced in Jin Liu (2023) <arXiv:2302.03237v2>.
Maintained by Jin Liu. Last updated 4 months ago.
8.0 match 145 stars 6.91 score 16 scriptshemingnm
SESraster:Raster Randomization for Null Hypothesis Testing
Randomization of presence/absence species distribution raster data with or without including spatial structure for calculating standardized effect sizes and testing null hypothesis. The randomization algorithms are based on classical algorithms for matrices (Gotelli 2000, <doi:10.2307/177478>) implemented for raster data.
Maintained by Neander Marcel Heming. Last updated 5 months ago.
null-modelsrandomizationrasterspatialspatial-analysisspecies-distribution-modelling
8.3 match 7 stars 6.61 score 32 scripts 2 dependentsropensci
occCite:Querying and Managing Large Biodiversity Occurrence Datasets
Facilitates the gathering of biodiversity occurrence data from disparate sources. Metadata is managed throughout the process to facilitate reporting and enhanced ability to repeat analyses.
Maintained by Hannah L. Owens. Last updated 5 months ago.
biodiversity-databiodiversity-informaticsbiodiversity-standardscitationsmuseum-collection-specimensmuseum-collectionsmuseum-metadata
7.5 match 23 stars 7.30 score 43 scriptsnovartis
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.
7.0 match 13 stars 7.76 score 105 scripts 5 dependentslbbe-software
fitdistrplus:Help to Fit of a Parametric Distribution to Non-Censored or Censored Data
Extends the fitdistr() function (of the MASS package) with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left censored, right censored and interval censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit estimation (MGE) and maximum spacing estimation (MSE) methods (available only for non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction to parametric estimation.
Maintained by Aurélie Siberchicot. Last updated 12 days ago.
3.4 match 54 stars 16.15 score 4.5k scripts 153 dependentsr-lidar
lidR:Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.
Maintained by Jean-Romain Roussel. Last updated 1 months ago.
alsforestrylaslazlidarpoint-cloudremote-sensingopenblascppopenmp
3.8 match 623 stars 14.47 score 844 scripts 8 dependentsr-forge
survey:Analysis of Complex Survey Samples
Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase and multiphase subsampling designs. Graphics. PPS sampling without replacement. Small-area estimation. Dual-frame designs.
Maintained by "Thomas Lumley". Last updated 6 months ago.
3.9 match 1 stars 13.94 score 13k scripts 232 dependentsjmgirard
circumplex:Analysis and Visualization of Circular Data
Circumplex models, which organize constructs in a circle around two underlying dimensions, are popular for studying interpersonal functioning, mood/affect, and vocational preferences/environments. This package provides tools for analyzing and visualizing circular data, including scoring functions for relevant instruments and a generalization of the bootstrapped structural summary method from Zimmermann & Wright (2017) <doi:10.1177/1073191115621795> and functions for creating publication-ready tables and figures from the results.
Maintained by Jeffrey Girard. Last updated 5 months ago.
circularcircumplexdata-analysisggplot2interpersonalpsychologyrcpparmadillotidyverseopenblascppopenmp
8.3 match 11 stars 6.54 score 52 scriptsegenn
rtemis:Machine Learning and Visualization
Advanced Machine Learning and Visualization. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and interactive graphics.
Maintained by E.D. Gennatas. Last updated 1 months ago.
data-sciencedata-visualizationmachine-learningmachine-learning-libraryvisualization
7.5 match 145 stars 7.09 score 50 scripts 2 dependentsrstudio
bigD:Flexibly Format Dates and Times to a Given Locale
Format dates and times flexibly and to whichever locales make sense. Parses dates, times, and date-times in various formats (including string-based ISO 8601 constructions). The formatting syntax gives the user many options for formatting the date and time output in a precise manner. Time zones in the input can be expressed in multiple ways and there are many options for formatting time zones in the output as well. Several of the provided helper functions allow for automatic generation of locale-aware formatting patterns based on date/time skeleton formats and standardized date/time formats with varying specificity.
Maintained by Richard Iannone. Last updated 12 days ago.
datedatetimeeasy-to-usei18ntime
5.7 match 19 stars 9.46 score 1 scripts 112 dependentspharmaverse
admiralonco:Oncology Extension Package for ADaM in 'R' Asset Library
Programming oncology specific 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>). The package is an extension package of the 'admiral' package.
Maintained by Stefan Bundfuss. Last updated 2 months ago.
6.1 match 32 stars 8.66 score 30 scriptssthawinke
oosse:Out-of-Sample R² with Standard Error Estimation
Estimates out-of-sample R² through bootstrap or cross-validation as a measure of predictive performance. In addition, a standard error for this point estimate is provided, and confidence intervals are constructed.
Maintained by Stijn Hawinkel. Last updated 6 months ago.
12.3 match 4 stars 4.30 score 5 scriptsropensci
outcomerate:AAPOR Survey Outcome Rates
Standardized survey outcome rate functions, including the response rate, contact rate, cooperation rate, and refusal rate. These outcome rates allow survey researchers to measure the quality of survey data using definitions published by the American Association of Public Opinion Research (AAPOR). For details on these standards, see AAPOR (2016) <https://www.aapor.org/Standards-Ethics/Standard-Definitions-(1).aspx>.
Maintained by Rafael Pilliard Hellwig. Last updated 4 years ago.
aapordisposition-codespeer-reviewedstandardssurvey
11.0 match 5 stars 4.78 score 24 scriptssbgraves237
Ecdat:Data Sets for Econometrics
Data sets for econometrics, including political science.
Maintained by Spencer Graves. Last updated 4 months ago.
7.2 match 2 stars 7.25 score 740 scripts 3 dependentsxfim
ggmcmc:Tools for Analyzing MCMC Simulations from Bayesian Inference
Tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables, and functions to work with hierarchical/multilevel batches of parameters (Fernández-i-Marín, 2016 <doi:10.18637/jss.v070.i09>).
Maintained by Xavier Fernández i Marín. Last updated 2 years ago.
bayesian-data-analysisggplot2graphicaljagsmcmcstan
4.3 match 112 stars 12.02 score 1.6k scripts 8 dependentsflrd
standardlastprofile:Data Package for BDEW Standard Load Profiles in Electricity
Data on standard load profiles from the German Association of Energy and Water Industries (BDEW Bundesverband der Energie- und Wasserwirtschaft e.V.) in a tidy format. The data and methodology are described in VDEW (1999), "Repräsentative VDEW-Lastprofile", <https://www.bdew.de/media/documents/1999_Repraesentative-VDEW-Lastprofile.pdf>. The package also offers an interface for generating a standard load profile over a user-defined period. For the algorithm, see VDEW (2000), "Anwendung der Repräsentativen VDEW-Lastprofile step-by-step", <https://www.bdew.de/media/documents/2000131_Anwendung-repraesentativen_Lastprofile-Step-by-step.pdf>.
Maintained by Markus Döring. Last updated 8 months ago.
13.9 match 1 stars 3.70 score 4 scriptsr-forge
car:Companion to Applied Regression
Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.
Maintained by John Fox. Last updated 5 months ago.
3.4 match 15.29 score 43k scripts 901 dependentsr-forge
sandwich:Robust Covariance Matrix Estimators
Object-oriented software for model-robust covariance matrix estimators. Starting out from the basic robust Eicker-Huber-White sandwich covariance methods include: heteroscedasticity-consistent (HC) covariances for cross-section data; heteroscedasticity- and autocorrelation-consistent (HAC) covariances for time series data (such as Andrews' kernel HAC, Newey-West, and WEAVE estimators); clustered covariances (one-way and multi-way); panel and panel-corrected covariances; outer-product-of-gradients covariances; and (clustered) bootstrap covariances. All methods are applicable to (generalized) linear model objects fitted by lm() and glm() but can also be adapted to other classes through S3 methods. Details can be found in Zeileis et al. (2020) <doi:10.18637/jss.v095.i01>, Zeileis (2004) <doi:10.18637/jss.v011.i10> and Zeileis (2006) <doi:10.18637/jss.v016.i09>.
Maintained by Achim Zeileis. Last updated 2 months ago.
3.4 match 14.92 score 11k scripts 887 dependentsalexanderrobitzsch
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 16 days ago.
missing-datamultiple-imputationopenblascpp
5.6 match 16 stars 9.16 score 542 scripts 9 dependentshwborchers
pracma:Practical Numerical Math Functions
Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.
Maintained by Hans W. Borchers. Last updated 1 years ago.
4.1 match 29 stars 12.34 score 6.6k scripts 931 dependentsnicwir
QurvE:Robust and User-Friendly Analysis of Growth and Fluorescence Curves
High-throughput analysis of growth curves and fluorescence data using three methods: linear regression, growth model fitting, and smooth spline fit. Analysis of dose-response relationships via smoothing splines or dose-response models. Complete data analysis workflows can be executed in a single step via user-friendly wrapper functions. The results of these workflows are summarized in detailed reports as well as intuitively navigable 'R' data containers. A 'shiny' application provides access to all features without requiring any programming knowledge. The package is described in further detail in Wirth et al. (2023) <doi:10.1038/s41596-023-00850-7>.
Maintained by Nicolas T. Wirth. Last updated 1 years ago.
8.3 match 25 stars 6.00 score 7 scriptsgabferreira
phyloraster:Evolutionary Diversity Metrics for Raster Data
Phylogenetic Diversity (PD, Faith 1992), Evolutionary Distinctiveness (ED, Isaac et al. 2007), Phylogenetic Endemism (PE, Rosauer et al. 2009; Laffan et al. 2016), and Weighted Endemism (WE, Laffan et al. 2016) for presence-absence raster. Faith, D. P. (1992) <doi:10.1016/0006-3207(92)91201-3> Isaac, N. J. et al. (2007) <doi:10.1371/journal.pone.0000296> Laffan, S. W. et al. (2016) <doi:10.1111/2041-210X.12513> Rosauer, D. et al. (2009) <doi:10.1111/j.1365-294X.2009.04311.x>.
Maintained by Gabriela Alves-Ferreira. Last updated 16 days ago.
8.8 match 7 stars 5.66 score 33 scriptsalistaire47
passport:Travel Smoothly Between Country Name and Code Formats
Smooths the process of working with country names and codes via powerful parsing, standardization, and conversion utilities arranged in a simple, consistent API. Country name formats include multiple sources including the Unicode Common Locale Data Repository (CLDR, <http://cldr.unicode.org/>) common-sense standardized names in hundreds of languages.
Maintained by Edward Visel. Last updated 4 years ago.
country-codescountry-datacountry-names
8.1 match 35 stars 6.17 score 28 scripts 1 dependentsaalfons
robustHD:Robust Methods for High-Dimensional Data
Robust methods for high-dimensional data, in particular linear model selection techniques based on least angle regression and sparse regression. Specifically, the package implements robust least angle regression (Khan, Van Aelst & Zamar, 2007; <doi:10.1198/016214507000000950>), (robust) groupwise least angle regression (Alfons, Croux & Gelper, 2016; <doi:10.1016/j.csda.2015.02.007>), and sparse least trimmed squares regression (Alfons, Croux & Gelper, 2013; <doi:10.1214/12-AOAS575>).
Maintained by Andreas Alfons. Last updated 9 months ago.
7.0 match 10 stars 7.06 score 174 scripts 8 dependentsbioc
DEGreport:Report of DEG analysis
Creation of ready-to-share figures of differential expression analyses of count data. It integrates some of the code mentioned in DESeq2 and edgeR vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene.
Maintained by Lorena Pantano. Last updated 5 months ago.
differentialexpressionvisualizationrnaseqreportwritinggeneexpressionimmunooncologybioconductordifferential-expressionqcreportrna-seqsmallrna
5.2 match 24 stars 9.42 score 354 scripts 1 dependentskolesarm
dfadjust:Degrees of Freedom Adjustment for Robust Standard Errors
Computes small-sample degrees of freedom adjustment for heteroskedasticity robust standard errors, and for clustered standard errors in linear regression. See Imbens and Kolesár (2016) <doi:10.1162/REST_a_00552> for a discussion of these adjustments.
Maintained by Michal Kolesár. Last updated 3 months ago.
8.5 match 31 stars 5.75 score 12 scriptsinsightsengineering
chevron:Standard TLGs for Clinical Trials Reporting
Provide standard tables, listings, and graphs (TLGs) libraries used in clinical trials. This package implements a structure to reformat the data with 'dunlin', create reporting tables using 'rtables' and 'tern' with standardized input arguments to enable quick generation of standard outputs. In addition, it also provides comprehensive data checks and script generation functionality.
Maintained by Joe Zhu. Last updated 24 days ago.
clinical-trialsgraphslistingsnestreportingtables
5.9 match 12 stars 8.24 score 12 scriptskjhealy
gssrdoc:Document General Social Survey Variable
The General Social Survey (GSS) is a long-running, mostly annual survey of US households. It is administered by the National Opinion Research Center (NORC). This package contains the a tibble with information on the survey variables, together with every variable documented as an R help page. For more information on the GSS see \url{http://gss.norc.org}.
Maintained by Kieran Healy. Last updated 11 months ago.
21.4 match 2.28 score 38 scriptslisalibungan
shapeR:Collection and Analysis of Otolith Shape Data
Studies otolith shape variation among fish populations. Otoliths are calcified structures found in the inner ear of teleost fish and their shape has been known to vary among several fish populations and stocks, making them very useful in taxonomy, species identification and to study geographic variations. The package extends previously described software used for otolith shape analysis by allowing the user to automatically extract closed contour outlines from a large number of images, perform smoothing to eliminate pixel noise, choose from conducting either a Fourier or wavelet transform to the outlines and visualize the mean shape. The output of the package are independent Fourier or wavelet coefficients which can be directly imported into a wide range of statistical packages in R. The package might prove useful in studies of any two dimensional objects.
Maintained by Lisa Anne Libungan. Last updated 7 years ago.
11.0 match 9 stars 4.45 score 21 scripts