Summarize Bayesian process-model diagnostics

Collects model availability, optional approximate leave-one-out summaries, posterior diagnostics, and (only when explicitly requested) a Bayes-factor comparison. The function does not treat any one diagnostic as proof of the substantive process interpretation.

Usage

bayesian_process_diagnostics_dashboard(
  ...,
  model_names = NULL,
  compute_loo = TRUE,
  compute_bayes_factor = FALSE,
  posterior_summary = TRUE
)

Arguments

...

Fitted `brmsfit` objects.

model_names

Optional model labels.

compute_loo

Whether to compute approximate leave-one-out diagnostics.

compute_bayes_factor

Whether to attempt a Bayes factor. This requires exactly two suitable brms models and typically models fitted with `save_pars = save_pars(all = TRUE)`.

posterior_summary

Whether to collect posterior convergence summaries when package `posterior` is available.

Value

An `eye_bayesian_process_dashboard` object.