bprobgHsSS: Internal Function

Description Author(s)

View source: R/bprobgHsSS.r

Description

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

Author(s)

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


SemiParBIVProbit documentation built on June 20, 2017, 9:03 a.m.

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