Check integration point adequacy — check

Compare integration results at the current n_int against a doubled resolution to assess numerical accuracy. Large discrepancies indicate that n_int should be increased.

Usage

check_integration(
  data,
  ...,
  cor = NULL,
  cor_adjust = NULL,
  check_joint = TRUE,
  verbose = TRUE
)

Arguments

data: An mlumr_data object with integration points
...: Distribution specifications (same as passed to add_integration())
cor: Correlation matrix (same as passed to add_integration())
cor_adjust: Adjustment method (same as passed to add_integration())
check_joint: If TRUE (default), also compare pairwise correlation matrices between the current and doubled n_int, and the maximum per-AgD-row absolute deviation from the user-supplied cor. The pairwise comparison catches cases where marginals converge but joint dependence structure does not (rare in practice for QMC with sensible cor_adjust but worth flagging when n_int is small).
verbose: Logical; if FALSE, suppresses printed diagnostic messages.

Value

A list with components marginals (the original data frame returned by previous versions) and, if check_joint = TRUE, correlations – a data frame of pairwise covariate correlations at the current and doubled n_int for each AgD row. Printed with a pass/warn verdict.