estfun.gmnl

It extracts the gradient for each observation evaluated at the estimated parameters for an object of class <code>gmnl</code>.

An implementation of maximum simulated likelihood method for the
estimation of multinomial logit models with random coefficients as presented by Sarrias and Daziano (2017) <doi:10.18637/jss.v079.i02>.
Specifically, it allows estimating models with continuous heterogeneity
such as the mixed multinomial logit and the generalized multinomial logit.
It also allows estimating models with discrete heterogeneity such as the
latent class and the mixed-mixed multinomial logit model.

Mauricio Sarrias

gmnl

Multinomial Logit Models with Random Parameters

Ricardo Daziano

Yves Croissant

estfun.gmnl function

<dl><dt>x</dt>
<dd>a fitted model of class <code>gmnl</code>.</dd>
<dt>...</dt>
<dd>other arguments. Ignored.</dd></dl>

Arguments

Gradient for Observations — estfun.gmnl

<dl>

<dt>x</dt>
<dd>a fitted model of class <code>gmnl</code>.</dd>


<dt>...</dt>
<dd>other arguments. Ignored.</dd>

</dl>

estfun.gmnl: Gradient for Observations

Description

Usage

Value

Arguments

Details

References