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 (or marginal_inference in case of marginal_estimates_table).

```
ensemble_estimates_table(
samples,
parameters,
probs = c(0.025, 0.95),
title = NULL,
footnotes = NULL,
warnings = NULL,
transform_factors = FALSE,
transform_orthonormal = FALSE,
formula_prefix = TRUE
)
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
)
ensemble_estimates_empty_table(
probs = c(0.025, 0.95),
title = NULL,
footnotes = NULL,
warnings = NULL
)
ensemble_inference_empty_table(title = NULL, footnotes = NULL, warnings = NULL)
ensemble_summary_empty_table(title = NULL, footnotes = NULL, warnings = NULL)
ensemble_diagnostics_empty_table(
title = NULL,
footnotes = NULL,
warnings = NULL
)
marginal_estimates_table(
samples,
inference,
parameters,
probs = c(0.025, 0.95),
logBF = FALSE,
BF01 = FALSE,
title = NULL,
footnotes = NULL,
warnings = NULL,
formula_prefix = TRUE
)
```

- samples
posterior samples created by mix_posteriors

- parameters
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

- probs
quantiles for parameter estimates

- title
title to be added to the table

- footnotes
footnotes to be added to the table

- warnings
warnings to be added to the table

- transform_factors
whether factors with orthonormal/meandif prior distribution should be transformed to differences from the grand mean

- transform_orthonormal
(to be depreciated) whether factors with orthonormal prior distributions should be transformed to differences from the grand mean

- formula_prefix
whether the parameter prefix from formula should be printed. Defaults to

`TRUE`

.- inference
model inference created by ensemble_inference

- logBF
whether the Bayes factor should be on log scale

- BF01
whether the Bayes factor should be inverted

- models
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- remove_spike_0
whether prior distributions equal to spike at 0 should be removed from the

`prior_list`

- short_name
whether the prior distribution names should be shortened. Defaults to

`FALSE`

.

`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'.