Function reference • rstanarm

About rstanarm These pages provides a summary of the functionality available in 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(<ppd>)`	In-sample or out-of-sample predictive errors
`predictive_interval(<stanreg>)` `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
`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`	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

Reference

About rstanarm

Fitting models

Methods

Additional documentation