Creates estimate summaries based on posterior distributions created by mix_posteriors, inference summaries based on inference created by ensemble_inference, or ensemble summary/diagnostics based on a list of models_inference models.

ensemble_estimates_table(
samples,
parameters,
probs = c(0.025, 0.95),
title = NULL,
footnotes = NULL,
warnings = NULL
)

ensemble_inference_table(
inference,
parameters,
logBF = FALSE,
BF01 = FALSE,
title = NULL,
footnotes = NULL,
warnings = NULL
)

ensemble_summary_table(
models,
parameters,
logBF = FALSE,
BF01 = FALSE,
title = NULL,
footnotes = NULL,
warnings = NULL,
remove_spike_0 = TRUE,
short_name = FALSE
)

ensemble_diagnostics_table(
models,
parameters,
title = NULL,
footnotes = NULL,
warnings = NULL,
remove_spike_0 = TRUE,
short_name = FALSE
)

## Arguments

samples posterior samples created by mix_posteriors character vector of parameters (or a named list with of character vectors for summary and diagnostics tables) specifying the parameters (and their grouping) for the summary table quantiles for parameter estimates title to be added to the table footnotes to be added to the table warnings to be added to the table model inference created by ensemble_inference whether the Bayes factor should be on log scale whether the Bayes factor should be inverted list of models_inference model objects, each of which containing a list of priors and inference object, The inference must be a named list with information about the model: model number m_number, marginal likelihood marglik, prior and posterior probability prior_prob and post_prob, inclusion Bayes factor inclusion_BF, and fit summary generated by runjags_estimates_table for the diagnostics table whether prior distributions equal to spike at 0 should be removed from the prior_list whether the prior distribution names should be shortened. Defaults to FALSE.

## Value

ensemble_estimates_table returns a table with the model-averaged estimates, ensemble_inference_table returns a table with the prior and posterior probabilities and inclusion Bayes factors, ensemble_summary_table returns a table with overview of the models included in the ensemble, and ensemble_diagnostics_table returns an overview of the MCMC diagnostics for the models included in the ensemble. All of the tables are objects of class 'BayesTools_table'.