bprobgHsDiscr1: Internal Function
In GJRM: Generalised Joint Regression Modelling
View source: R/bprobgHsDiscr1.r
bprobgHsDiscr1 R Documentation
Internal Function
Description
It provides the log-likelihood, gradient and observed information matrix for
penalized/unpenalized maximum likelihood optimization when copula models with binary and discrete margins are employed.
Author(s)
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
GJRM documentation built on Oct. 25, 2024, 5:07 p.m.
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View source: R/bprobgHsDiscr1.r
| bprobgHsDiscr1 | R Documentation |
Internal Function
Description
It provides the log-likelihood, gradient and observed information matrix for penalized/unpenalized maximum likelihood optimization when copula models with binary and discrete 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.
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