Fingerprint the prior-generative configuration of a fitted model

Two experiments that share the same prior-generative structure (same residual structure, same beta/tau/LKJ priors, same declared random-effect block structure, same fixed-effect design-column definitions, same D) can safely REUSE a prior predictive check's results rather than rerunning simulate_probit_prior_predictive for every experiment – prior predictive checking depends only on the generative structure, never on the fitted posterior. If ANY component changes (a prior, a scaling, the declared block structure), the fingerprint changes and any cached result must be invalidated.

Usage

compute_prior_predictive_fingerprint(fitted_model)

Arguments

fitted_model

A fitted model object as returned by fit_bayesian_multivariate_probit.

Value

List with fingerprint (a single character hash via rlang::hash(), already an anumaan dependency – no new package dependency introduced) and components (the exact named list that was hashed, for audit/debugging).