VSLCMparamCategorical-class

<dl>
 <dt>pi</dt>
<dd>numeric. Proportions of the mixture components.</dd> <dt>alpha</dt>
<dd>list. Parameters of the multinomial distributions.</dd>
</dl>

Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here <doi:10.1007/s11222-016-9670-1>). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.

Mohammed Sedki

VarSelLCM

Variable Selection for Model-Based Clustering of Mixed-Type Data
Set with Missing Values

Matthieu Marbac

VSLCMparamCategorical-class function

<dl>
 <dt>pi</dt>
<dd>numeric. Proportions of the mixture components.</dd>

 <dt>alpha</dt>
<dd>list. Parameters of the multinomial distributions.</dd>


</dl>

VSLCMparamCategorical-class: Constructor of `VSLCMparamCategorical` class

Description

Arguments

Examples