Check a fitted longitudinal GAMLSS-copula model — check

check_model() turns diagnostics into compact basic automated checks for broad applied use. It does not replace visual inspection, but it provides a stable first pass over convergence, marginal calibration, residual dependence, and scoring summaries.

Usage

check_model(
  object,
  include_vcov = FALSE,
  include_plots = FALSE,
  dependence_cor_cutoff = 0.25,
  ...
)

Arguments

object: A fitted gamlss.longitudinal object.
include_vcov: Logical; include variance-covariance inference metadata via summary.gamlss.longitudinal().
include_plots: Logical; include standard diagnostic plot objects in check$plots. Visual review should usually use plot(object) or the explicit diagnostic helpers instead.
dependence_cor_cutoff: Absolute lag-1 Rosenblatt normal-score residual correlation above which the dependence check is flagged. The default is a review threshold rather than a formal hypothesis test.
...: Passed to summary.gamlss.longitudinal() when include_vcov is TRUE.

Value

An object of class gamlss_longitudinal_check, including a compact basic_checks table, a full checks table, a filtered warnings table for failed checks, and overall basic_checks_passed and basic_checks_result fields.