FLXMCmvbinary

FLXbclust

This is a model driver for <code>flexmix</code> implementing
 model-based clustering of binary data.

cluster

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

FLXMCmvbinary 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>. Only the left-hand side (response) of
 the formula is used. Default is to use the original
 <code>flexmix</code> model
 formula.</dd> <dt>truncated</dt>
<dd>logical, if <code>TRUE</code> the observations for the
 pattern with only zeros are missing and the truncated likelihood is
 optimized using an EM-algorithm.</dd></dl>

Arguments

Friedrich Leisch and Bettina Gruen

Author

FlexMix Binary Clustering Driver — FLXMCmvbinary

<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>. Only the left-hand side (response) of
 the formula is used. Default is to use the original
 <code>flexmix</code> model
 formula.</dd>

 <dt>truncated</dt>
<dd>logical, if <code>TRUE</code> the observations for the
 pattern with only zeros are missing and the truncated likelihood is
 optimized using an EM-algorithm.</dd>

</dl>

FLXMCmvbinary: FlexMix Binary Clustering Driver

Description

Usage

Value

Arguments

Author

Details

See Also