Weighted Log-Link (Relative-Risk) Binomial Regression Hessian, Standalone (C++)

Computes the observation-weighted Hessian matrix of the weighted log-likelihood of the constrained log-link binomial regression model documented in full at fast_log_binomial_regression_cpp, at arbitrary caller-supplied beta (not necessarily the MLE), with each observation's contribution multiplied by weights_r[i], via a numerical (central finite-difference 4-point stencil, step \(h = 10^{-4}\)) approximation — not an analytic second derivative. Exported standalone — independent of any optimizer run — for direct numerical diagnostics at a specific parameter value.

Usage

get_log_binomial_regression_weighted_hessian_cpp(X, y_r, weights_r, beta)

Arguments

X

A numeric matrix of predictors.

y_r

A binary (0/1) numeric vector of responses.

weights_r

A nonnegative numeric vector of observation weights.

beta

A numeric vector of coefficients \(\beta\) at which to evaluate the Hessian.

Value

The finite-difference-approximated weighted Hessian matrix at beta.

A numeric matrix representing the weighted Hessian.

See also

get_log_binomial_regression_weighted_score_cpp for the corresponding weighted gradient at the same point; get_log_binomial_regression_hessian_cpp for the unweighted version; fast_log_binomial_regression_cpp for the full model documentation.