bitsgHs: Internal Function
In SemiParSampleSel: Semi-Parametric Sample Selection Modelling with Continuous or Discrete Response
Description
It provides the quantites needed to calculate the log-likelihood, gradient and Hessian matrix for
penalized or unpenalized maximum likelihood optimization, for a number of copula models.
Author(s)
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
SemiParSampleSel documentation built on May 2, 2019, 6:35 a.m.
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Description
It provides the quantites needed to calculate the log-likelihood, gradient and Hessian matrix for penalized or unpenalized maximum likelihood optimization, for a number of copula models.
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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