bprobgHsPO: Internal Function
In GJRM: Generalised Joint Regression Modelling
bprobgHsPO R Documentation
Internal Function
Description
It provides the log-likelihood, gradient and observed or expected information matrix for
penalized/unpenalized maximum likelihood optimization when bivariate probit models with partial
observability are employed.
Author(s)
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
GJRM documentation built on July 9, 2023, 7:15 p.m.
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| bprobgHsPO | R Documentation |
Internal Function
Description
It provides the log-likelihood, gradient and observed or expected information matrix for penalized/unpenalized maximum likelihood optimization when bivariate probit models with partial observability 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.
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