lcModel-data-filters

bootSample

trainFold

testFold

The data filters are applied by latrend prior to model estimation. These filters are used in latrendBoot and latrendCV.

internal

A framework for clustering longitudinal datasets in a standardized way.
The package provides an interface to existing R packages for clustering longitudinal univariate trajectories, facilitating reproducible and transparent analyses.
Additionally, standard tools are provided to support cluster analyses, including repeated estimation, model validation, and model assessment.
The interface enables users to compare results between methods, and to implement and evaluate new methods with ease.
The 'akmedoids' package is available from <https://github.com/MAnalytics/akmedoids>.

Niek Den Teuling

latrend

A Framework for Clustering Longitudinal Data

Steffen Pauws

Edwin van den Heuvel

Koninklijke Philips N.V. 

lcModel-data-filters function

<dl><dt>data</dt>
<dd>The <code>data.frame</code> representing the model dataset.</dd>
<dt>id</dt>
<dd>The identifier variable name, see idVariable.</dd>
<dt>seed</dt>
<dd>Optional seed for ensuring reproducibility.</dd>
<dt>fold</dt>
<dd>The fold to select.</dd>
<dt>folds</dt>
<dd>Total number of folds to create.</dd></dl>

Arguments

Data filters for lcModel — lcModel-data-filters

<dl>

<dt>data</dt>
<dd>The <code>data.frame</code> representing the model dataset.</dd>


<dt>id</dt>
<dd>The identifier variable name, see idVariable.</dd>


<dt>seed</dt>
<dd>Optional seed for ensuring reproducibility.</dd>


<dt>fold</dt>
<dd>The fold to select.</dd>


<dt>folds</dt>
<dd>Total number of folds to create.</dd>

</dl>

lcModel-data-filters: Data filters for lcModel

Description

Usage

Value

Arguments

See Also