bprobNP

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

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

bprobNP: Internal Function

Description

Arguments