hassanpazira/BFI v3.3.0

BFI 3.3.0

on GitHub

Added an optional formula/data interface to MAP.estimation() and inv.prior.cov(), while retaining the original y/X interface. The statistical estimation and federated aggregation procedures remain unchanged.

Updated S3 class handling to distinguish local and federated BFI objects while preserving compatibility with existing print(), summary(), coef(), and vcov() methods.

Corrected Gaussian regression inference by consistently using the log-residual-variance parameterization for local estimation, curvature calculations, and federated aggregation.

Retained residual-variance estimates on the original scale in the reported coefficients.

Expanded numerical validation and unit tests for Gaussian regression, including curvature and covariance calculations.

Improved numerical stability of binomial regression by using a stable softplus expression for the negative log-likelihood and plogis() for the curvature calculation.

Corrected propensity-score calculations in second-round Gaussian and binomial treatment-effect analyses by applying plogis() directly to the linear predictor. Improved numerical stability of propensity-score calculations in survival models.

Added validation to reject unsupported cross-precision terms between regression coefficients and log-residual variance in Gaussian prior precision matrices.