assess_recovery: Simulation-study assessment helpers

In bayesqm: Bayesian Q Methodology: Probabilistic Factor Analysis

Simulation-study assessment helpers

Description

assess_recovery() compares a point estimate and optional posterior draws to a known loading truth, returning RMSE, per-factor RMSE, bias, Tucker's congruence, credible-interval coverage, width, and Gneiting-Raftery interval score. assess_classification() compares a logical flag matrix to the true factor assignments using optimal permutation matching.

Usage

assess_recovery(Lambda_hat, Lambda_true, Lambda_draws = NULL, prob = 0.95)

assess_classification(flags, Lambda_true)

Arguments

Lambda_hat	Estimated loading matrix (N x K).
Lambda_true	True loading matrix.
Lambda_draws	Optional array of shape ⁠[T, N, K]⁠ of posterior draws, used for coverage / interval metrics.
prob	Credible-interval probability.
flags	Logical matrix of factor assignments.

Value

assess_recovery() returns a list of metrics; assess_classification() returns a list with accuracy and per_factor.

bayesqm documentation built on June 18, 2026, 1:07 a.m.