Calculate LOO-CV for an mlumr_fit — calculate

Computes approximate leave-one-out cross-validation (PSIS-LOO, Vehtari, Gelman, Gabry 2017) using the pointwise log-likelihoods stored by the Stan models. Returns a loo object from the loo package.

Usage

calculate_loo(object, ...)

Arguments

object: An mlumr_fit object.
...: Additional arguments passed to loo::loo.array().

Value

An object of class psis_loo (see loo::loo()).

Details

Pareto-k diagnostics: values > 0.7 indicate observations for which the PSIS approximation is unreliable; the printed output flags these. Typical remedies are running more iterations, using moment_match = TRUE, or (for highly influential AgD rows) refitting without the offending observation to check sensitivity.

Note

AgD rows are treated as independent observations. Each AgD row contributes one column to the pointwise log_lik matrix. If two or more AgD rows come from the same study (e.g. subgroup summaries within a single trial) the PSIS-LOO approximation does not account for the within-study clustering; effective sample sizes are inflated and Pareto-k warnings are understated. For clustered AgD, corroborate with prior_sensitivity() or refit omitting suspect rows to check the influence on the posterior.

Examples

if (FALSE) { # \dontrun{
loo_spfa <- calculate_loo(fit_spfa)
print(loo_spfa)
} # }