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Transform gMAP to draws objects

Source: R/posterior.R
draws-RBesT.Rd

[Experimental]

Transform a gMAP object to a format supported by the posterior package.

Usage

# S3 method for class 'gMAP'
as_draws(x, variable = NULL, regex = FALSE, inc_warmup = FALSE, ...)

# S3 method for class 'gMAP'
as_draws_matrix(x, variable = NULL, regex = FALSE, inc_warmup = FALSE, ...)

# S3 method for class 'gMAP'
as_draws_array(x, variable = NULL, regex = FALSE, inc_warmup = FALSE, ...)

# S3 method for class 'gMAP'
as_draws_df(x, variable = NULL, regex = FALSE, inc_warmup = FALSE, ...)

# S3 method for class 'gMAP'
as_draws_list(x, variable = NULL, regex = FALSE, inc_warmup = FALSE, ...)

# S3 method for class 'gMAP'
as_draws_rvars(x, variable = NULL, regex = FALSE, inc_warmup = FALSE, ...)

Arguments

x

A gMAP object.

variable

A character vector providing the variables to extract. By default, all variables are extracted.

regex

Logical; Should variable be treated as a (vector of) regular expressions? Any variable in x matching at least one of the regular expressions will be selected. Defaults to FALSE.

inc_warmup

Should warmup draws be included? Defaults to FALSE.

...

Arguments passed to individual methods (if applicable).

Details

To subset iterations, chains, or draws, use the posterior::subset_draws() method after transforming the input object to a draws object.

The function is experimental as the set of exported posterior variables are subject to updates.

See also

posterior::draws() posterior::subset_draws()

Examples

## Setting up dummy sampling for fast execution of example
## Please use 4 chains and 20x more warmup & iter in practice
.user_mc_options <- options(RBesT.MC.warmup=50, RBesT.MC.iter=100,
                            RBesT.MC.chains=2, RBesT.MC.thin=1)


set.seed(34563)
map_AS <- gMAP(cbind(r, n - r) ~ 1 | study,
  family = binomial,
  data = AS,
  tau.dist = "HalfNormal", tau.prior = 1,
  beta.prior = 2
)
#> Assuming default prior location   for beta: 0
#> Warning: The largest R-hat is 1.31, indicating chains have not mixed.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#r-hat
#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#bulk-ess
#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#tail-ess
#> Warning: Maximal Rhat > 1.1. Consider increasing RBesT.MC.warmup MCMC parameter.
#> Final MCMC sample equivalent to less than 1000 independent draws.
#> Please consider increasing the MCMC simulation size.

post_AS <- as_draws(map_AS)

## Recover user set sampling defaults
options(.user_mc_options)