Validate a GLM design bundle (y, X, n_trials) at a fitter's front door.

Shared by the flagship drivers (tulpa_nested_laplace(), tulpa_gibbs(), the re_cov fitters) so nrow(X) == length(y) and length(n_trials) == length(y) are enforced in one place – otherwise a mismatched n_trials (as.integer(NULL) -> integer(0)) reaches the C++ kernel silently.

Usage

.validate_glm_design(y, X, n_trials, where)

Arguments

y, X

Response vector and design matrix.

n_trials

Binomial denominators, or NULL (defaults to 1 per row).

where

Caller name for the error message.

Value

List list(N, n_trials) with n_trials coerced to a length-N integer vector.

Details

The finite-input guard is enforced here too, which is what carries it to every door taking this bundle. Left to each door it was wired into three of them and not into tulpa_nested_laplace(), where an NA response is not rejected but absorbed: every grid cell returns converged = FALSE with log_marginal = 0, the softmax over those weights is uniform, a fit comes back, and the retention step then finds no Q on any cell and reports the user's own missing data to them as a package defect (gcol33/tulpa#613).