Function reference • rstan

All functions
`As.mcmc.list()`	Create an mcmc.list from a stanfit object
`Rhat()` `ess_bulk()` `ess_tail()`	Convergence and efficiency diagnostics for Markov Chains
`check_hmc_diagnostics()` `check_divergences()` `check_treedepth()` `check_energy()` `get_divergent_iterations()` `get_max_treedepth_iterations()` `get_num_leapfrog_per_iteration()` `get_num_divergent()` `get_num_max_treedepth()` `get_bfmi()` `get_low_bfmi_chains()`	Check HMC diagnostics after sampling
`expose_stan_functions()` `get_rng()` `get_stream()`	Expose user-defined Stan functions to R for testing and simulation
`extract_sparse_parts()`	Extract the compressed representation of a sparse matrix
`lookup()`	Look up the Stan function that corresponds to a R function or name.
`makeconf_path()`	Obtain the full path of file `Makeconf`
`monitor()` `print(<simsummary>)` `[`(<simsummary>)	Compute summaries of MCMC draws and monitor convergence
`nlist()`	Created named lists
`rstan-plotting-functions`	RStan Plotting Functions
`print(<stanfit>)`	Print a summary for a fitted model represented by a `stanfit` object
`read_rdump()`	Read data in an R dump file to a list
`rstan-package` `rstan`	RStan --- the R interface to Stan
`rstan.package.skeleton`	Create a Skeleton for a New Source Package with Stan Programs
`rstan_options()`	Set and read options used in RStan
`sbc()` `plot(<sbc>)` `print(<sbc>)`	Simulation Based Calibration (sbc)
`set_cppo()`	Defunct function to set the compiler optimization level
`sflist2stanfit()`	Merge a list of stanfit objects into one
`stan()`	Fit a model with Stan
`read_stan_csv()`	Read CSV files of samples generated by (R)Stan into a `stanfit` object
`stan_demo()`	Demonstrate examples included in Stan
`stan_model()`	Construct a Stan model
`stan_plot()` `stan_trace()` `stan_scat()` `stan_hist()` `stan_dens()` `stan_ac()` `quietgg()`	ggplot2 for RStan
`stan_diag()` `stan_par()` `stan_rhat()` `stan_ess()` `stan_mcse()`	RStan Diagnostic plots
`rstan_gg_options()` `rstan_ggtheme_options()`	Set default appearance options
`stan_rdump()`	Dump the data for a Stan model to R dump file in the limited format that Stan can read.
`stan_version()`	Obtain the version of Stan
`stanc()` `stanc_builder()`	Translate Stan model specification to C++ code
`stanfit-class` `stanfit` `show,stanfit-method` `get_cppo_mode` `get_cppo_mode,stanfit-method` `get_stancode` `get_stancode,stanfit-method` `get_stanmodel` `get_stanmodel,stanfit-method` `get_seed` `get_seed,stanfit-method` `get_seeds` `get_seeds,stanfit-method` `get_inits` `get_inits,stanfit-method` `get_posterior_mean` `get_posterior_mean,stanfit-method` `get_elapsed_time` `get_elapsed_time,stanfit-method` `get_logposterior` `get_logposterior,stanfit-method` `get_adaptation_info` `get_adaptation_info,stanfit-method` `get_sampler_params` `get_sampler_params,stanfit,logical-method`	Class `stanfit`: fitted Stan model
`extract(<stanfit>)`	Extract samples from a fitted Stan model
`log_prob(<stanfit>)` `grad_log_prob(<stanfit>)` `get_num_upars(<stanfit>)` `constrain_pars(<stanfit>)` `unconstrain_pars(<stanfit>)`	`log_prob` and `grad_log_prob` functions
`loo_moment_match(<stanfit>)`	Moment matching for efficient approximate leave-one-out cross-validation (LOO)
`loo(<stanfit>)`	Approximate leave-one-out cross-validation
`pairs(<stanfit>)`	Create a matrix of output plots from a `stanfit` object
`plot(<stanfit>,<missing>)`	Plots for stanfit objects
`summary(<stanfit>)`	Summary method for stanfit objects
`traceplot(<stanfit>)`	Markov chain traceplots
`as.array(<stanfit>)` `as.matrix(<stanfit>)` `as.data.frame(<stanfit>)` `is.array(<stanfit>)` `dim(<stanfit>)` `dimnames(<stanfit>)` `names(<stanfit>)` `names<-`(<stanfit>)	Create array, matrix, or data.frame objects from samples in a `stanfit` object
`stanmodel-class` `get_cppcode` `get_cxxflags` `get_cppcode,stanmodel-method` `get_cxxflags,stanmodel-method` `get_stancode,stanmodel-method` `show,stanmodel-method`	Class representing model compiled from C++
`gqs(<stanmodel>)`	Draw samples of generated quantities from a Stan model
`optimizing(<stanmodel>)`	Obtain a point estimate by maximizing the joint posterior
`sampling(<stanmodel>)`	Draw samples from a Stan model
`vb(<stanmodel>)`	Run Stan's variational algorithm for approximate posterior sampling

Reference

All functions