bprobNRE

It provides the log-likelihood, gradient and observed information matrix for 
penalized or unpenalized maximum likelihood optimization in the presense
of bivariate normal random effects.

Routine for fitting bivariate probit models with semiparametric predictors (including linear, nonlinear and random effects) in the presence of correlated error equations, endogeneity or sample selection. Bivariate copula models are also supported.

bprobNRE: Internal Function

Description

Arguments