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rstanarm (version 2.14.1)

Bayesian Applied Regression Modeling via Stan

Description

Estimates pre-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.

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Version

Install

install.packages('rstanarm')

Monthly Downloads

10,505

Version

2.14.1

License

GPL (>= 3)

Maintainer

Ben Goodrich

Last Published

January 17th, 2017

Functions in rstanarm (2.14.1)

model.matrix.stanreg

model.matrix method for stanreg objects
neg_binomial_2

Family function for negative binomial GLMs
stan_gamm4

Bayesian generalized linear additive models with group-specific terms via Stan
posterior_linpred

Posterior distribution of the linear predictor
posterior_predict.stanreg

Draw from posterior predictive distribution
stan_glm

Bayesian generalized linear models via Stan
terms.stanreg

terms method for stanreg objects
loo.stanreg

Leave-one-out (LOO) and K-fold cross-validation
stan_polr

Bayesian ordinal regression models via Stan
model.frame.stanreg

model.frame method for stanreg objects
example_model

Example model
adapt_delta

Target average acceptance probability
stanreg-objects

Fitted model objects
rstanarm-package

Applied Regression Modeling via RStan
priors

Prior distributions and options
stan_betareg

Bayesian beta regression models via Stan
stan_biglm

Bayesian regularized linear but big models via Stan
log_lik.stanreg

Pointwise log-likelihood matrix
prior_summary.stanreg

Summarize the priors used for an rstanarm model
print.stanreg

Print method for stanreg objects
get_y

Extract X, Y or Z from a stanreg object
stan_aov

Bayesian regularized linear models via Stan
stan_glmer

Bayesian generalized linear models with group-specific terms via Stan
family.stanreg

family method for stanreg objects
predict.stanreg

Predict method for stanreg objects
formula.stanreg

formula method for stanreg objects
print.kfold

Print method for kfold
pp_check.stanreg

Graphical posterior predictive checks
se

Extract standard errors
pp_validate

Model validation via simulation
shinystan

Using the ShinyStan GUI with rstanarm models