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: | 2.17.4 |
| Depends: | R (≥ 3.2.0), Rcpp (≥ 0.12.0), methods |
| Imports: | bayesplot (≥ 1.5.0), ggplot2 (≥ 2.2.1), lme4 (≥ 1.1-8), loo (≥ 2.0.0), Matrix (≥ 1.2-13), nlme (≥ 3.1-124), rstan (≥ 2.17.2), rstantools (≥ 1.4.0), shinystan (≥ 2.3.0), stats, survival (≥ 2.40.1), utils |
| LinkingTo: | StanHeaders (≥ 2.17.1), rstan (≥ 2.17.2), BH (≥ 1.65.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0) |
| Suggests: | betareg, data.table (≥ 1.10.0), digest, gridExtra, HSAUR3, knitr (≥ 1.15.1), MASS, mgcv (≥ 1.8-13), rmarkdown, roxygen2, testthat (≥ 1.0.2) |
| Published: | 2018-04-13 |
| 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: | http://discourse.mc-stan.org, http://mc-stan.org/, http://mc-stan.org/rstanarm/ |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make, pandoc (>= 1.12.3), pandoc-citeproc |
| Citation: | rstanarm citation info |
| Materials: | NEWS |
| CRAN checks: | rstanarm results |
| Reference manual: | rstanarm.pdf |
| Vignettes: |
stan_aov: ANOVA Models stan_betareg: Models for Rate/Proportion Data stan_glm: GLMs for Binary and Binomial Data stan_glm: GLMs for Continuous Data stan_glm: GLMs for Count Data stan_glmer: GLMs with Group-Specific Terms stan_jm: Joint Models for Longitudinal and Time-to-Event Data stan_lm: Regularized Linear Models stan_polr: Ordinal Models Hierarchical Partial Pooling Prior Distributions How to Use the rstanarm Package |
| Package source: | rstanarm_2.17.4.tar.gz |
| Windows binaries: | r-devel: rstanarm_2.17.4.zip, r-release: rstanarm_2.17.4.zip, r-oldrel: rstanarm_2.17.4.zip |
| OS X binaries: | r-release: rstanarm_2.17.4.tgz, r-oldrel: rstanarm_2.17.4.tgz |
| Old sources: | rstanarm archive |
| Reverse depends: | evidence |
| Reverse imports: | glmmfields, projpred, psycho, tidyposterior |
| Reverse suggests: | bayesplot, bridgesampling, broom, jtools, loo, lsmeans, merTools, RBesT, rstantools, shinystan, sjPlot, sjstats |
| Reverse enhances: | emmeans |
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