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rstanarm: Bayesian Applied Regression Modeling via Stan

Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.

Version:2.32.2
Depends:R (≥ 3.4.0),Rcpp (≥ 0.12.0), methods
Imports:bayesplot (≥ 1.7.0),ggplot2 (≥ 2.2.1),lme4 (≥ 1.1-8),loo (≥ 2.1.0),Matrix (≥ 1.2-13),nlme (≥ 3.1-124),posterior,rstan (≥ 2.32.0),rstantools (≥ 2.1.0),shinystan (≥ 2.3.0), stats,survival (≥ 2.40.1),RcppParallel (≥ 5.0.1), utils,reformulas
LinkingTo:StanHeaders (≥ 2.32.0),rstan (≥ 2.32.0),BH (≥1.72.0-2),Rcpp (≥ 0.12.0),RcppEigen (≥ 0.3.3.3.0),RcppParallel (≥ 5.0.1)
Suggests:biglm,betareg,data.table (≥ 1.10.0),digest,gridExtra,HSAUR3,knitr (≥ 1.15.1),MASS,mgcv (≥ 1.8-13),rmarkdown,roxygen2,StanHeaders (≥ 2.21.0),testthat (≥ 1.0.2),gamm4,shiny,V8
Published:2025-09-30
DOI:10.32614/CRAN.package.rstanarm
Author:Jonah Gabry [aut], Imad Ali [ctb], Sam Brilleman [ctb], Jacqueline Buros Novik [ctb] (R/stan_jm.R), AstraZeneca [ctb] (R/stan_jm.R), Trustees of Columbia University [cph], Simon Wood [cph] (R/stan_gamm4.R), R Core Deveopment Team [cph] (R/stan_aov.R), Douglas Bates [cph] (R/pp_data.R), Martin Maechler [cph] (R/pp_data.R), Ben Bolker [cph] (R/pp_data.R), Steve Walker [cph] (R/pp_data.R), Brian Ripley [cph] (R/stan_aov.R, R/stan_polr.R), William Venables [cph] (R/stan_polr.R), Paul-Christian Burkner [cph] (R/misc.R), Ben Goodrich [cre, aut]
Maintainer:Ben Goodrich <benjamin.goodrich at columbia.edu>
BugReports:https://github.com/stan-dev/rstanarm/issues
License:GPL (≥ 3)
URL:https://mc-stan.org/rstanarm/,https://discourse.mc-stan.org
NeedsCompilation:yes
SystemRequirements:GNU make, pandoc (>= 1.12.3), pandoc-citeproc
Citation:rstanarm citation info
Materials:NEWS
In views:Bayesian,MixedModels,Survival
CRAN checks:rstanarm results

Documentation:

Reference manual:rstanarm.html ,rstanarm.pdf
Vignettes:Probabilistic A/B Testing with rstanarm (source,R code)
stan_aov: ANOVA Models (source,R code)
stan_betareg: Models for Rate/Proportion Data (source,R code)
stan_glm: GLMs for Binary and Binomial Data (source,R code)
stan_glm: GLMs for Continuous Data (source,R code)
stan_glm: GLMs for Count Data (source,R code)
stan_glmer: GLMs with Group-Specific Terms (source,R code)
stan_jm: Joint Models for Longitudinal and Time-to-Event Data (source,R code)
stan_lm: Regularized Linear Models (source,R code)
MRP with rstanarm (source,R code)
stan_polr: Ordinal Models (source,R code)
Hierarchical Partial Pooling (source,R code)
Prior Distributions (source,R code)
How to Use the rstanarm Package (source,R code)

Downloads:

Package source: rstanarm_2.32.2.tar.gz
Windows binaries: r-devel:rstanarm_2.32.2.zip, r-release:rstanarm_2.32.2.zip, r-oldrel:rstanarm_2.32.2.zip
macOS binaries: r-release (arm64):rstanarm_2.32.2.tgz, r-oldrel (arm64):rstanarm_2.32.2.tgz, r-release (x86_64):rstanarm_2.32.2.tgz, r-oldrel (x86_64):rstanarm_2.32.2.tgz
Old sources: rstanarm archive

Reverse dependencies:

Reverse depends:AuxSurvey,evidence,fbst
Reverse imports:BayesERtools,bayesrules,IRexamples,JMbdirect,jmBIG,SIMPLE.REGRESSION,tidyposterior,webSDM
Reverse suggests:afex,bayesMeanScale,bayesplot,BayesPostEst,bayestestR,bridgesampling,broom.helpers,broom.mixed,conformalbayes,correlation,datawizard,effectsize,embed,fastml,ggeffects,INLAjoint,insight,loo,marginaleffects,merTools,modelbased,modelsummary,orbital,parameters,performance,projpred,RBesT,rdss,report,SAMprior,see,shinybrms,shinystan,sjPlot,tidyAML,tidybayes,valueprhr
Reverse enhances:emmeans,interactions,jtools

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=rstanarmto link to this page.

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