FLXMRmultinom

Model driver for fitting mixtures of multinomial logit models.

models

regression

A general framework for finite mixtures of regression
models using the EM algorithm is implemented. The E-step and all
data handling are provided, while the M-step can be supplied by the
user to easily define new models. Existing drivers implement
mixtures of standard linear models, generalized linear models and
model-based clustering.

Bettina Gruen

flexmix

Flexible Mixture Modeling

Friedrich Leisch

Deepayan Sarkar

Frederic Mortier

Nicolas Picard

FLXMRmultinom function

<dl> <dt>formula</dt>
<dd>A formula which is interpreted relative to the formula
 specified in the call to <code>flexmix</code> using
 <code><a href="/link/update.formula?package=flexmix&version=2.3-19" data-mini-rdoc="flexmix::update.formula">update.formula</a></code>. Default is to use the original
 <code>flexmix</code> model
 formula.</dd> <dt>...</dt>
<dd>Additional arguments to be passed to <code>nnet.default</code>.</dd></dl>

Arguments

Author

To ensure identifiability repeated measurements are
 necessary. Sufficient conditions are given in Gruen and Leisch (2008).

Warning

FlexMix Interface to Multiomial Logit Models — FLXMRmultinom

<dl>

 <dt>formula</dt>
<dd>A formula which is interpreted relative to the formula
 specified in the call to <code>flexmix</code> using
 <code><a href='https://rdrr.io/r/stats/update.formula.html'>update.formula</a></code>. Default is to use the original
 <code>flexmix</code> model
 formula.</dd>

 <dt>...</dt>
<dd>Additional arguments to be passed to <code>nnet.default</code>.</dd>

</dl>

FLXMRmultinom: FlexMix Interface to Multiomial Logit Models

Description

Usage

Value

Arguments

Author

Warning

Details

References

See Also