VSLCMdataInteger-class

<dl class="dl-horizontal">
 <dt>n</dt><dd>number of observations</dd>
 <dt>d</dt><dd>number of variables</dd>
 <dt>data</dt><dd>matrix of observations (one row = one observation)</dd>
 <dt>notNA</dt><dd>matrix of logical (1:observed, 0:unobserved)</dd>
 <dt>priors</dt><dd>hyper-parameters of the prior distributions</dd>
</dl>@examples
 getSlots("VSLCMdataInteger")

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

VSLCMdataInteger-class function

<dl class='dl-horizontal'>
 <dt>n</dt><dd>number of observations</dd>
 <dt>d</dt><dd>number of variables</dd>
 <dt>data</dt><dd>matrix of observations (one row = one observation)</dd>
 <dt>notNA</dt><dd>matrix of logical (1:observed, 0:unobserved)</dd>
 <dt>priors</dt><dd>hyper-parameters of the prior distributions</dd>
</dl>@examples
 getSlots("VSLCMdataInteger")

Constructor of <code><a href='<a href='VSLCMdataInteger'></a>'>VSLCMdataInteger</a></code> class — VSLCMdataInteger-class

Constructor of <code><a href='<a href='VSLCMdataInteger'></a>'>VSLCMdataInteger</a></code> class

Constructor of <code><a href="/link/?package=VarSelLCM&version=2.1.1" vslcmdatainteger'="" data-mini-rdoc="VarSelLCM::"></a>'>VSLCMdataInteger</code> class

VSLCMdataInteger-class: Constructor of `'>VSLCMdataInteger` class

Description

Arguments