glm with a formula and a data.frame).
The set of models supported by pp_check function for graphical posterior
predictive checks and the posterior_predict function to
easily estimate the effect of specific manipulations of predictor variables
or to predict the outcome in a training set.
The objects returned by the stanreg objects. In addition to all of the
typical methods defined for fitted model
objects, stanreg objects can be passed to the loo
function in the launch_shinystan function in the priors for an overview of the various choices the user can
make for prior distributions. The package vignettes also provide
examples of using many of the available priors as well as more detailed
descriptions of some of the novel priors used by Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari,
A., and Rubin, D. B. (2013). Bayesian Data Analysis. Chapman & Hall/CRC
Press, London, third edition.
Gelman, A. and Hill, J. (2007). Data Analysis Using
Regression and Multilevel/Hierarchical Models. Cambridge University Press,
Cambridge, UK.
Stan Development Team. (2015). Stan Modeling Language Users Guide and
Reference Manual.
Vehtari, A., Gelman, A., and Gabry, J. (2016). Practical Bayesian model
evaluation using leave-one-out cross-validation and WAIC.
stanreg-objects and stanreg-methods for
details on the fitted model objects returned by the modeling functions.
plots for the various plots that can be used
to explore and check fitted models.