lcApproxModel-class

lcApproxModel

fitted.lcApproxModel

predictForCluster,lcApproxModel-method

approx models have defined cluster trajectories at fixed moments in time, which should be interpolated
For a correct implementation, <code>lcApproxModel</code> requires the extending class to implement <code>clusterTrajectories(at=NULL)</code>
to return the fixed cluster trajectories

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. 

lcApproxModel-class function

<dl><dt>object</dt>
<dd>The <code>lcModel</code> object.</dd>
<dt>...</dt>
<dd>Additional arguments.</dd>
<dt>clusters</dt>
<dd>Optional cluster assignments per id. If unspecified, a <code>matrix</code> is returned containing the cluster-specific predictions per column.</dd>
<dt>newdata</dt>
<dd>A <code>data.frame</code> of trajectory data for which to compute trajectory assignments.</dd>
<dt>cluster</dt>
<dd>The cluster name (as <code>character</code>) to predict for.</dd>
<dt>what</dt>
<dd>The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying <code>what = 'mb'</code>.</dd>
<dt>approxFun</dt>
<dd>Function to interpolate between measurement moments, <a href="/link/approx?package=latrend&version=1.6.2" data-mini-rdoc="latrend::approx">approx</a>() by default.</dd></dl>

Arguments

lcApproxModel class — lcApproxModel-class

<dl>

<dt>object</dt>
<dd>The <code>lcModel</code> object.</dd>


<dt>...</dt>
<dd>Additional arguments.</dd>


<dt>clusters</dt>
<dd>Optional cluster assignments per id. If unspecified, a <code>matrix</code> is returned containing the cluster-specific predictions per column.</dd>


<dt>newdata</dt>
<dd>A <code>data.frame</code> of trajectory data for which to compute trajectory assignments.</dd>


<dt>cluster</dt>
<dd>The cluster name (as <code>character</code>) to predict for.</dd>


<dt>what</dt>
<dd>The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying <code>what = 'mb'</code>.</dd>


<dt>approxFun</dt>
<dd>Function to interpolate between measurement moments, <a href='https://rdrr.io/r/stats/approxfun.html'>approx</a>() by default.</dd>

</dl>

lcApproxModel-class: lcApproxModel class

Description

Usage

Arguments