CRAN/E | rstanarm

rstanarm

Bayesian Applied Regression Modeling via Stan

Installation

About

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.

Citation rstanarm citation info
mc-stan.org/rstanarm/
discourse.mc-stan.org
System requirements GNU make, pandoc (>= 1.12.3), pandoc-citeproc
Bug report File report

Key Metrics

Version 2.32.1
R ≥ 3.4.0
Published 2024-01-18 99 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks rstanarm results

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Maintainer

Maintainer

Ben Goodrich

benjamin.goodrich@columbia.edu

Authors

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

Material

NEWS
Reference manual
Package source

In Views

Bayesian
MixedModels
Survival

Vignettes

Probabilistic A/B Testing with rstanarm
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
MRP with rstanarm
stan_polr: Ordinal Models
Hierarchical Partial Pooling
Prior Distributions
How to Use the rstanarm Package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

rstanarm archive

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

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

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

Reverse Depends

evidence
fbst

Reverse Imports

BayesPostEst
bayesrules
eefAnalytics
IRexamples
jmBIG
tidyposterior
webSDM

Reverse Suggests

afex
bayesplot
bayestestR
bridgesampling
broom.helpers
broom.mixed
conformalbayes
correlation
datawizard
effectsize
embed
ggeffects
insight
loo
marginaleffects
merTools
modelbased
modelsummary
parameters
performance
projpred
RBesT
rdss
report
SAMprior
see
shinybrms
shinystan
sjPlot
tidyAML
tidybayes

Reverse Enhances

emmeans
interactions
jtools