bprobgHs: Internal Function

Description Author(s)

View source: R/bprobgHs.r

Description

It provides the log-likelihood, gradient and observed/Fisher information matrix for penalized/unpenalized maximum likelihood optimization when copula models with binary outcomes are employed.

Author(s)

Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk


KironmoyDas/KD-STAT0035-GMupdate documentation built on Feb. 15, 2021, 12:17 a.m.