logLik.SemiParBIV

logLik.ggmtrust

logLik.lmc

It extracts the log-likelihood for a fitted <code>gjrm</code> model.

logLik

Routines for fitting various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations' errors association, endogeneity, non-random sample selection or partial observability.

Giampiero Marra

GJRM

Generalised Joint Regression Modelling

logLik.SemiParBIV function

<dl>
 
 
<dt>object</dt>
<dd>A fitted <code>gjrm</code> object.</dd>
<dt>...</dt>
<dd>Un-used for this function.</dd></dl>

Arguments

Maintainer: Giampiero Marra <a href="/link/giampiero.marra%40ucl.ac.uk?package=GJRM&version=0.2-6.5" data-mini-rdoc="GJRM::giampiero.marra@ucl.ac.uk">giampiero.marra@ucl.ac.uk</a>

Author

Extract the log likelihood for a fitted copula model — logLik.SemiParBIV

<dl>
 
 
<dt>object</dt>
<dd>A fitted <code>gjrm</code> object.</dd>


<dt>...</dt>
<dd>Un-used for this function.</dd>



</dl>

Maintainer: Giampiero Marra <a href='mailto:giampiero.marra@ucl.ac.uk'>giampiero.marra@ucl.ac.uk</a>

logLik.SemiParBIV: Extract the log likelihood for a fitted copula model

Description

Usage

Value

Arguments

Author

Details

See Also