as_mixed_posteriors: Export BayesTools JAGS model posterior distribution as...

In FBartos/BayesTools: Tools for Bayesian Analyses

Export BayesTools JAGS model posterior distribution as model-average posterior distributions via mix_posteriors

Description

Creates a model-averages posterior distributions on a single model that allows mimicking the mix_posteriors functionality. This function is useful when the model-averaged ensemble is based on prior_spike_and_slab or prior_mixture priors - the model-averaging is done within the model.

Usage

as_mixed_posteriors(
  model,
  parameters,
  conditional = NULL,
  conditional_rule = "AND",
  force_plots = FALSE
)

Arguments

model	model fit via the JAGS_fit function
parameters	vector of parameters names for which inference should be drawn
conditional	a character vector of parameters to be conditioned on
conditional_rule	a character string specifying the rule for conditioning. Either "AND" or "OR". Defaults to "AND".
force_plots	temporal argument allowing to generate conditional posterior samples suitable for prior and posterior plots. Only available when conditioning on a single parameter.

Value

as_mix_posteriors returns a named list of mixed posterior distributions (either a vector of matrix).

See Also

mix_posteriors

FBartos/BayesTools documentation built on Jan. 20, 2025, 8:15 a.m.