bprobgHsContSS: Internal Function
In GJRM: Generalised Joint Regression Modelling
View source: R/bprobgHsContSS.r
bprobgHsContSS R Documentation
Internal Function
Description
It provides the log-likelihood, gradient and observed information matrix for
penalized/unpenalized maximum likelihood optimization when copula sample selection models with continuous margins are employed.
Author(s)
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
GJRM documentation built on Oct. 25, 2024, 5:07 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
View source: R/bprobgHsContSS.r
| bprobgHsContSS | R Documentation |
Internal Function
Description
It provides the log-likelihood, gradient and observed information matrix for penalized/unpenalized maximum likelihood optimization when copula sample selection models with continuous margins are employed.
Author(s)
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.