Package index • rstanarm

About rstanarm

These pages provides a summary of the functionality available in rstanarm.

rstanarm rstanarm-package: Applied Regression Modeling via RStan
available-models: Modeling functions available in rstanarm
available-algorithms: Estimation algorithms available for rstanarm models

Fitting models

Functions for model fitting.

stan_betareg() stan_betareg.fit(): Bayesian beta regression models via Stan
stan_biglm() stan_biglm.fit(): Bayesian regularized linear but big models via Stan
stan_clogit(): Conditional logistic (clogit) regression models via Stan
stan_gamm4() plot_nonlinear(): Bayesian generalized linear additive models with optional group-specific terms via Stan
stan_glm() stan_glm.nb() stan_glm.fit(): Bayesian generalized linear models via Stan
stan_glmer() stan_lmer() stan_glmer.nb(): Bayesian generalized linear models with group-specific terms via Stan
stan_jm(): Bayesian joint longitudinal and time-to-event models via Stan
stan_aov() stan_lm() stan_lm.wfit() stan_lm.fit(): Bayesian regularized linear models via Stan
stan_mvmer(): Bayesian multivariate generalized linear models with correlated group-specific terms via Stan
stan_nlmer(): Bayesian nonlinear models with group-specific terms via Stan
stan_polr() stan_polr.fit(): Bayesian ordinal regression models via Stan
normal() student_t() cauchy() hs() hs_plus() laplace() lasso() product_normal() exponential() decov() lkj() dirichlet() R2() default_prior_intercept() default_prior_coef(): Prior distributions and options

Methods

Functions to work with fitted model objects.

stanreg-objects: Fitted model objects
as.matrix(<stanreg>) as.array(<stanreg>) as.data.frame(<stanreg>): Extract the posterior sample
bayes_R2(<stanreg>) loo_R2(<stanreg>): Compute a Bayesian version of R-squared or LOO-adjusted R-squared for regression models.
kfold(<stanreg>): K-fold cross-validation
launch_shinystan(<stanreg>): Using the ShinyStan GUI with rstanarm models
log_lik(<stanreg>) log_lik(<stanmvreg>) log_lik(<stanjm>): Pointwise log-likelihood matrix
loo(<stanreg>) waic(<stanreg>) loo_compare(<stanreg>) loo_compare(<stanreg_list>) loo_model_weights(<stanreg_list>) compare_models(): Information criteria and cross-validation
loo_predict(<stanreg>) loo_linpred(<stanreg>) loo_predictive_interval(<stanreg>): Compute weighted expectations using LOO
pairs(<stanreg>): Pairs method for stanreg objects
plot(<stanreg>): Plot method for stanreg objects
posterior_interval(<stanreg>): Posterior uncertainty intervals
posterior_linpred(<stanreg>) posterior_epred(<stanreg>): Posterior distribution of the (possibly transformed) linear predictor
posterior_predict(<stanreg>) posterior_predict(<stanmvreg>): Draw from posterior predictive distribution
posterior_vs_prior(): Juxtapose prior and posterior
pp_check(<stanreg>): Graphical posterior predictive checks
predict(<stanreg>): Predict method for stanreg objects
predictive_error(<stanreg>) predictive_error(<matrix>) predictive_error(<ppd>): In-sample or out-of-sample predictive errors
predictive_interval(<stanreg>) predictive_interval(<matrix>) predictive_interval(<ppd>): Predictive intervals
print(<stanreg>) print(<stanmvreg>): Print method for stanreg objects
prior_summary(<stanreg>): Summarize the priors used for an rstanarm model
as_draws(<stanreg>) as_draws_matrix(<stanreg>) as_draws_array(<stanreg>) as_draws_df(<stanreg>) as_draws_list(<stanreg>) as_draws_rvars(<stanreg>): Create a draws object from a stanreg object
nobs(<stanmvreg>) coef(<stanreg>) confint(<stanreg>) fitted(<stanreg>) nobs(<stanreg>) residuals(<stanreg>) se(<stanreg>) update(<stanreg>) vcov(<stanreg>) fixef(<stanreg>) ngrps(<stanreg>) nsamples(<stanreg>) ranef(<stanreg>) sigma(<stanreg>) VarCorr(<stanreg>): Methods for stanreg objects
summary(<stanreg>) print(<summary.stanreg>) as.data.frame(<summary.stanreg>) summary(<stanmvreg>) print(<summary.stanmvreg>): Summary method for stanreg objects
posterior_survfit(): Estimate subject-specific or standardised survival probabilities
posterior_traj(): Estimate the subject-specific or marginal longitudinal trajectory
ps_check(): Graphical checks of the estimated survival function
coef(<stanmvreg>) fitted(<stanmvreg>) residuals(<stanmvreg>) se(<stanmvreg>) formula(<stanmvreg>) update(<stanmvreg>) update(<stanjm>) fixef(<stanmvreg>) ngrps(<stanmvreg>) ranef(<stanmvreg>) sigma(<stanmvreg>): Methods for stanmvreg objects
plot(<predict.stanjm>): Plot the estimated subject-specific or marginal longitudinal trajectory
plot(<survfit.stanjm>) plot_stack_jm(): Plot the estimated subject-specific or marginal survival function

Additional documentation

Misc. other help pages.

rstanarm-datasets kidiq roaches wells bball1970 bball2006 mortality tumors radon pbcLong pbcSurv: Datasets for rstanarm examples
example_model: Example model
example_jm: Example joint longitudinal and time-to-event model
stanreg_list() stanmvreg_list() stanjm_list() print(<stanreg_list>): Create lists of fitted model objects, combine them, or append new models to existing lists of models.
adapt_delta: adapt_delta: Target average acceptance probability
QR-argument: The QR argument
neg_binomial_2(): Family function for negative binomial GLMs
prior_options(): Deprecated functions
logit() invlogit(): Logit and inverse logit