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.

Generalised Joint Regression Modelling

package-ubuntu-20.04-r-4.0.5#cran#GJRM-0.2-4

<p>It takes a fitted model object and produces some 
diagnostic information about the fitting procedure.
</p>

<table summary="R argblock"><tr valign="top">
<td><code>x</code></td>
<td>
<p><code>gjrm</code> object.</p>
</td>
</tr></table>

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

<p><code><a href="gamlss.html">gamlss</a></code>, <code><a href="gjrm.html">gjrm</a></code>
</p>

package-ubuntu-20.04-r-4.0.5#cran#GJRM-0.2-4#docs#conv.check

conv.check

Description

Usage

Arguments

Author(s)

See Also

GJRM

We don't support your browser anymore