VSLCMpartitions-class

<dl>
 <dt>zMAP</dt>
<dd>numeric. A vector indicating the class membership of each individual by using the MAP rule computed for the best model with its maximum likelihood estimates.</dd> <dt>zOPT</dt>
<dd>numeric. Partition maximizing the integrated complete-data likelihood of the selected model.</dd> <dt>tik</dt>
<dd>numeric. Fuzzy partition computed for the best model with its maximum likelihood estimates.</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

VSLCMpartitions-class function

<dl>
 <dt>zMAP</dt>
<dd>numeric. A vector indicating the class membership of each individual by using the MAP rule computed for the best model with its maximum likelihood estimates.</dd>

 <dt>zOPT</dt>
<dd>numeric. Partition maximizing the integrated complete-data likelihood of the selected model.</dd>

 <dt>tik</dt>
<dd>numeric. Fuzzy partition computed for the best model with its maximum likelihood estimates.</dd>


</dl>

VSLCMpartitions-class: Constructor of `VSLCMpartitions` class

Description

Arguments

Examples