CLC-methods

CLC,REBMIX-method

CLC,REBMVNORM-method

a desired row number in <code>x@summary</code> for which the information criterion is calculated. The default value is <code>1</code>.

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Returns the classification likelihood criterion at <code>pos</code>.

information criterion

Random univariate and multivariate finite mixture model generation, estimation, clustering, latent class analysis and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, Gumbel, binomial, Poisson, Dirac or circular von Mises parametric families.

Marko Nagode

rebmix

Finite Mixture Modeling, Clustering & Classification

Branislav Panic

Jernej Klemenc

Simon Oman

CLC-methods function

<dl class="dl-horizontal">
<dt><code>signature(x = "REBMIX")</code></dt><dd>an object of class <code>REBMIX</code>.</dd>
<dt><code>signature(x = "REBMVNORM")</code></dt><dd>an object of class <code>REBMVNORM</code>.</dd>
</dl>

Methods

Classification Likelihood Criterion — CLC-methods

<dl class='dl-horizontal'>
<dt><code>signature(x = "REBMIX")</code></dt><dd>an object of class <code>REBMIX</code>.</dd>
<dt><code>signature(x = "REBMVNORM")</code></dt><dd>an object of class <code>REBMVNORM</code>.</dd>
</dl>

CLC-methods: Classification Likelihood Criterion

Description

Usage

Arguments

Methods

References