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rstan: R Interface to Stan

User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.

Version: 2.32.6
Depends: R (≥ 3.4.0), StanHeaders (≥ 2.32.0)
Imports: methods, stats4, inline (≥ 0.3.19), gridExtra (≥ 2.3), Rcpp (≥ 1.0.7), RcppParallel (≥ 5.1.4), loo (≥ 2.4.1), pkgbuild (≥ 1.2.0), QuickJSR, ggplot2 (≥ 3.3.5)
LinkingTo: Rcpp (≥ 1.0.7), RcppEigen (≥ 0.3.4.0.0), BH (≥ 1.75.0-0), StanHeaders (≥ 2.32.0), RcppParallel (≥ 5.1.4)
Suggests: testthat (≥ 3.0.4), parallel, KernSmooth, shinystan, bayesplot, rmarkdown, rstantools, rstudioapi, Matrix, knitr, coda, V8
Published: 2024-03-05
DOI: 10.32614/CRAN.package.rstan
Author: Jiqiang Guo [aut], Jonah Gabry [aut], Ben Goodrich [cre, aut], Andrew Johnson [aut], Sebastian Weber [aut], Hamada S. Badr ORCID iD [aut], Daniel Lee [ctb], Krzysztof Sakrejda [ctb], Modrak Martin [ctb], Trustees of Columbia University [cph], Oleg Sklyar [cph] (R/cxxfunplus.R), The R Core Team [cph] (R/pairs.R, R/dynGet.R), Jens Oehlschlaegel-Akiyoshi [cph] (R/pairs.R), John Maddock [cph] (gamma.hpp), Paul Bristow [cph] (gamma.hpp), Nikhar Agrawal [cph] (gamma.hpp), Christopher Kormanyos [cph] (gamma.hpp), Bronder Steve [ctb]
Maintainer: Ben Goodrich <benjamin.goodrich at columbia.edu>
BugReports: https://github.com/stan-dev/rstan/issues/
License: GPL (≥ 3)
URL: https://mc-stan.org/rstan/, https://discourse.mc-stan.org
NeedsCompilation: yes
SystemRequirements: GNU make, pandoc
Citation: rstan citation info
Materials: NEWS
In views: Bayesian, MixedModels
CRAN checks: rstan results

Documentation:

Reference manual: rstan.pdf
Vignettes: Simulation Based Calibration
Interfacing with External C++ Code
RStan
stanfit objects

Downloads:

Package source: rstan_2.32.6.tar.gz
Windows binaries: r-devel: rstan_2.32.6.zip, r-release: rstan_2.32.6.zip, r-oldrel: rstan_2.32.6.zip
macOS binaries: r-release (arm64): rstan_2.32.6.tgz, r-oldrel (arm64): rstan_2.32.6.tgz, r-release (x86_64): rstan_2.32.6.tgz, r-oldrel (x86_64): rstan_2.32.6.tgz
Old sources: rstan archive

Reverse dependencies:

Reverse depends: banocc, BASiCStan, BayesianPlatformDesignTimeTrend, bayesvl, bmscstan, clinDR, dfped, DrBats, edstan, evidence, fergm, GPP, GPRMortality, HCT, iCARH, JMbayes, MADPop, MIXFIM, ppcseq, tmbstan, varian, visit, walker
Reverse imports: adnuts, AovBay, baggr, bakR, baldur, BANOVA, bayclumpr, bayes4psy, bayesdfa, bayesforecast, bayesGAM, BayesGmed, BayesGP, BayesGrowth, BayesSenMC, bayesZIB, bbmix, BCEA, beanz, BeeGUTS, bellreg, bennu, Bernadette, BINtools, bistablehistory, bkmrhat, blavaan, bmgarch, bmggum, bmlm, bmstdr, BPrinStratTTE, breathteststan, brms, brxx, bsitar, bsynth, bws, CARME, CausalQueries, cbq, chkptstanr, cloneRate, ClustIRR, CNVRG, conStruct, ctsem, dclone, DCPO, decontX, densEstBayes, disbayes, dynamite, EcoEnsemble, eDNAjoint, eggCounts, EloSteepness, EpiNow2, fcirt, FlexReg, flps, footBayes, gastempt, geostan, glmmfields, glmmPen, glmmrBase, greencrab.toolkit, GUD, hbamr, hBayesDM, historicalborrowlong, hsstan, HuraultMisc, hwep, idem, IgGeneUsage, imt, isotracer, jfa, lgpr, llbayesireg, LMMELSM, MCMCvis, measr, metaBMA, MetaStan, miniLNM, MIRES, mlts, mrbayes, multinma, multipleDL, mvgam, neodistr, networkscaleup, OncoBayes2, oncomsm, parTimeROC, pcFactorStan, pema, phacking, phylopairs, pivmet, PoolTestR, ProbBreed, prome, prophet, psBayesborrow, PStrata, publipha, rater, RBesT, rbioacc, rcbayes, Rlgt, rmBayes, rmsb, rmstBayespara, RoBTT, rPBK, rstanarm, rstanbdp, rstanemax, rts2, scMET, serosv, shinybrms, shinystan, spsurv, ssMousetrack, SSNbayes, StanMoMo, surveil, survstan, thurstonianIRT, tipsae, trialr, TriDimRegression, truncnormbayes, tsnet, ubms, WhiteLabRt, winputall, YPBP, YPPE, zoid
Reverse linking to: AovBay, baggr, bakR, baldur, BASiCStan, bayes4psy, bayesdfa, bayesforecast, bayesGAM, BayesGmed, BayesGrowth, BayesianPlatformDesignTimeTrend, BayesSenMC, bayesZIB, bbmix, beanz, BeeGUTS, bellreg, bennu, Bernadette, BINtools, bistablehistory, blavaan, bmgarch, bmggum, bmlm, bmstdr, BPrinStratTTE, breathteststan, bsynth, bws, CARME, CausalQueries, cbq, cloneRate, ClustIRR, CNVRG, conStruct, ctsem, DCPO, decontX, densEstBayes, disbayes, EcoEnsemble, eDNAjoint, eggCounts, EloSteepness, EpiNow2, fcirt, FlexReg, gastempt, geostan, glmmfields, glmmPen, glmmrBase, greencrab.toolkit, GUD, hbamr, hBayesDM, historicalborrowlong, hsstan, hwep, idem, IgGeneUsage, imt, isotracer, jfa, lgpr, LMMELSM, MADPop, measr, metaBMA, MetaStan, miniLNM, MIRES, mlts, mrbayes, multinma, multipleDL, networkscaleup, OncoBayes2, oncomsm, parTimeROC, pcFactorStan, pema, phacking, phylopairs, PoolTestR, ppcseq, ProbBreed, prome, prophet, psBayesborrow, publipha, rater, RBesT, rbioacc, rcbayes, Rlgt, rmBayes, rmsb, RoBTT, rPBK, rstanarm, rstanbdp, rstanemax, rts2, scMET, serosv, spsurv, ssMousetrack, StanMoMo, surveil, survstan, thurstonianIRT, tipsae, tmbstan, trialr, TriDimRegression, truncnormbayes, tsnet, ubms, visit, walker, WhiteLabRt, winputall, YPBP, YPPE, zoid
Reverse suggests: alien, bayesian, bayesImageS, bayesnec, bayesplot, BayesPostEst, bayestestR, BayesTools, bridgesampling, brms.mmrm, broom.mixed, compareMCMCs, finalfit, flocker, hmmTMB, loo, lorad, makemyprior, metabias, mice, modeltime, mpower, parameters, pcvr, pollimetry, PosteriorBootstrap, postpack, priorsense, rbmi, rstantools, runMCMCbtadjust, SoupX, StanHeaders, survHE, tidybayes, unifed
Reverse enhances: DHARMa, dsem, mrregression

Linking:

Please use the canonical form https://CRAN.R-project.org/package=rstan to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.