UnweightedKMeansClustering

Runs k-means clustering using implementation from
<code><a href="/link/kmeans?package=sharp&version=1.4.7" data-mini-rdoc="sharp::kmeans">kmeans</a></code>. This function is not using stability.

internal

In stability selection (N Meinshausen, P Bühlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>) and consensus clustering (S Monti et al (2003) <doi:10.1023/A:1023949509487>), resampling techniques are used to enhance the reliability of the results. In this package (B Bodinier et al (2025) <doi:10.18637/jss.v112.i05>), hyper-parameters are calibrated by maximising model stability, which is measured under the null hypothesis that all selection (or co-membership) probabilities are identical (B Bodinier et al (2023a) <doi:10.1093/jrsssc/qlad058> and B Bodinier et al (2023b) <doi:10.1093/bioinformatics/btad635>). Functions are readily implemented for the use of LASSO regression, sparse PCA, sparse (group) PLS or graphical LASSO in stability selection, and hierarchical clustering, partitioning around medoids, K means or Gaussian mixture models in consensus clustering.

Barbara Bodinier

sharp

Stability-enHanced Approaches using Resampling Procedures

UnweightedKMeansClustering function

<dl><dt>xdata</dt>
<dd>data matrix with observations as rows and variables as columns.</dd>
<dt>nc</dt>
<dd>matrix of parameters controlling the number of clusters in the
underlying algorithm specified in <code>implementation</code>. If <code>nc</code> is
not provided, it is set to <code>seq(1, tau*nrow(xdata))</code>.</dd>
<dt>...</dt>
<dd>additional parameters passed to <code><a href="/link/kmeans?package=sharp&version=1.4.7" data-mini-rdoc="sharp::kmeans">kmeans</a></code>.</dd></dl>

Arguments

Runs k-means clustering using implementation from
<code><a href='https://rdrr.io/r/stats/kmeans.html'>kmeans</a></code>. This function is not using stability.

Unweighted K-means clustering — UnweightedKMeansClustering

<dl>

<dt>xdata</dt>
<dd>data matrix with observations as rows and variables as columns.</dd>


<dt>nc</dt>
<dd>matrix of parameters controlling the number of clusters in the
underlying algorithm specified in <code>implementation</code>. If <code>nc</code> is
not provided, it is set to <code>seq(1, tau*nrow(xdata))</code>.</dd>


<dt>...</dt>
<dd>additional parameters passed to <code><a href='https://rdrr.io/r/stats/kmeans.html'>kmeans</a></code>.</dd>

</dl>

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UnweightedKMeansClustering: Unweighted K-means clustering

Description

Usage

Value

Arguments