bprobgHsContUniv

It provides the log-likelihood, gradient and observed information matrix for 
penalized or unpenalized maximum likelihood optimization, when fitting univariate models with continuous response.

Routine for fitting bivariate models for binary and continuous responses with linear and nonlinear effects in the presence of associated error equations, endogeneity, non-random sample selection or partial observability.

bprobgHsContUniv: Internal Function

Description

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