Extract quantities needed for plotting from model objects

Generics and methods for extracting quantities needed for plotting from various types of model objects. Currently methods are provided for stanfit (rstan), CmdStanMCMC (cmdstanr), and stanreg (rstanarm) objects, but adding new methods should be relatively straightforward.

Usage

log_posterior(object, ...)

nuts_params(object, ...)

rhat(object, ...)

neff_ratio(object, ...)

# S3 method for class 'stanfit'
log_posterior(object, inc_warmup = FALSE, ...)

# S3 method for class 'stanreg'
log_posterior(object, inc_warmup = FALSE, ...)

# S3 method for class 'CmdStanMCMC'
log_posterior(object, inc_warmup = FALSE, ...)

# S3 method for class 'stanfit'
nuts_params(object, pars = NULL, inc_warmup = FALSE, ...)

# S3 method for class 'stanreg'
nuts_params(object, pars = NULL, inc_warmup = FALSE, ...)

# S3 method for class 'list'
nuts_params(object, pars = NULL, ...)

# S3 method for class 'CmdStanMCMC'
nuts_params(object, pars = NULL, ...)

# S3 method for class 'stanfit'
rhat(object, pars = NULL, ...)

# S3 method for class 'stanreg'
rhat(object, pars = NULL, regex_pars = NULL, ...)

# S3 method for class 'CmdStanMCMC'
rhat(object, pars = NULL, ...)

# S3 method for class 'stanfit'
neff_ratio(object, pars = NULL, ...)

# S3 method for class 'stanreg'
neff_ratio(object, pars = NULL, regex_pars = NULL, ...)

# S3 method for class 'CmdStanMCMC'
neff_ratio(object, pars = NULL, ...)

Arguments

object

The object to use.

...

Arguments passed to individual methods.

inc_warmup

A logical scalar (defaulting to FALSE) indicating whether to include warmup draws, if applicable.

pars

An optional character vector of parameter names. For nuts_params() these will be NUTS sampler parameter names rather than model parameters. If pars is omitted all parameters are included.

regex_pars

An optional regular expression to use for parameter selection. Can be specified instead of pars or in addition to pars. When using pars for tidy parameter selection, the regex_pars argument is ignored since select helpers perform a similar function.

Value

log_posterior()

log_posterior() methods return a molten data frame (see reshape2::melt()). The data frame should have columns "Iteration" (integer), "Chain" (integer), and "Value" (numeric). See Examples, below.

nuts_params()

nuts_params() methods return a molten data frame (see reshape2::melt()). The data frame should have columns "Parameter" (factor), "Iteration" (integer), "Chain" (integer), and "Value" (numeric). See Examples, below.

rhat(), neff_ratio()

Methods return (named) vectors.

See also

MCMC-nuts, MCMC-diagnostics

Examples

# \dontrun{
library(rstanarm)
fit <- stan_glm(mpg ~ wt, data = mtcars, refresh = 0)

np <- nuts_params(fit)
head(np)
#>   Chain Iteration     Parameter     Value
#> 1     1         1 accept_stat__ 1.0000000
#> 2     1         2 accept_stat__ 0.9128983
#> 3     1         3 accept_stat__ 1.0000000
#> 4     1         4 accept_stat__ 0.9318817
#> 5     1         5 accept_stat__ 0.9799518
#> 6     1         6 accept_stat__ 0.9476718
tail(np)
#>       Chain Iteration Parameter    Value
#> 23995     4       995  energy__ 88.87303
#> 23996     4       996  energy__ 89.30687
#> 23997     4       997  energy__ 88.59940
#> 23998     4       998  energy__ 86.71444
#> 23999     4       999  energy__ 86.85860
#> 24000     4      1000  energy__ 87.95147

lp <- log_posterior(fit)
head(lp)
#>   Chain Iteration     Value
#> 1     1         1 -87.22566
#> 2     1         2 -87.77245
#> 3     1         3 -87.54427
#> 4     1         4 -88.95054
#> 5     1         5 -85.92995
#> 6     1         6 -86.47992
tail(lp)
#>      Chain Iteration     Value
#> 3995     4       995 -86.72768
#> 3996     4       996 -87.57157
#> 3997     4       997 -86.38115
#> 3998     4       998 -86.35389
#> 3999     4       999 -86.67260
#> 4000     4      1000 -87.41818
# }