Create BayesTools model tables

Creates model summary based on a model objects or provides estimates table for a runjags fit.

model_summary_table(
  model,
  model_description = NULL,
  title = NULL,
  footnotes = NULL,
  warnings = NULL,
  remove_spike_0 = TRUE,
  short_name = FALSE,
  formula_prefix = TRUE,
  remove_parameters = NULL
)

runjags_estimates_table(
  fit,
  transformations = NULL,
  title = NULL,
  footnotes = NULL,
  warnings = NULL,
  conditional = FALSE,
  remove_spike_0 = TRUE,
  transform_factors = FALSE,
  transform_orthonormal = FALSE,
  formula_prefix = TRUE,
  remove_inclusion = FALSE,
  remove_parameters = NULL
)

runjags_inference_table(
  fit,
  title = NULL,
  footnotes = NULL,
  warnings = NULL,
  formula_prefix = TRUE
)

JAGS_estimates_table(
  fit,
  transformations = NULL,
  title = NULL,
  footnotes = NULL,
  warnings = NULL,
  conditional = FALSE,
  remove_spike_0 = TRUE,
  transform_factors = FALSE,
  transform_orthonormal = FALSE,
  formula_prefix = TRUE,
  remove_inclusion = FALSE,
  remove_parameters = NULL
)

JAGS_inference_table(
  fit,
  title = NULL,
  footnotes = NULL,
  warnings = NULL,
  formula_prefix = TRUE
)

JAGS_summary_table(
  model,
  model_description = NULL,
  title = NULL,
  footnotes = NULL,
  warnings = NULL,
  remove_spike_0 = TRUE,
  short_name = FALSE,
  formula_prefix = TRUE,
  remove_parameters = NULL
)

model_summary_empty_table(
  model_description = NULL,
  title = NULL,
  footnotes = NULL,
  warnings = NULL
)

runjags_estimates_empty_table(title = NULL, footnotes = NULL, warnings = NULL)

runjags_inference_empty_table(title = NULL, footnotes = NULL, warnings = NULL)

JAGS_estimates_empty_table(title = NULL, footnotes = NULL, warnings = NULL)

JAGS_inference_empty_table(title = NULL, footnotes = NULL, warnings = NULL)

stan_estimates_table(
  fit,
  transformations = NULL,
  title = NULL,
  footnotes = NULL,
  warnings = NULL
)

Arguments

model: model object 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, and model inclusion Bayes factor inclusion_BF
model_description: named list with additional description to be added to the table
title: title to be added to the table
footnotes: footnotes to be added to the table
warnings: warnings to be added to the 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.
formula_prefix: whether the parameter prefix from formula should be printed. Defaults to TRUE.
remove_parameters: parameters to be removed from the summary. Defaults to NULL, i.e., including all parameters.
fit: runjags model fit
transformations: named list of transformations to be applied to specific parameters
conditional: summarizes estimates conditional on being included in the model for spike and slab priors. Defaults to FALSE.
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
remove_inclusion: whether estimates of the inclusion probabilities should be excluded from the summary table. Defaults to FALSE.

Value

model_summary_table returns a table with overview of the fitted model, runjags_estimates_table returns a table with MCMC estimates, and runjags_estimates_empty_table

returns an empty estimates table. All of the tables are objects of class 'BayesTools_table'.

Arguments

Value

See also