plot.variable_selection

Makes a barplot of selection proportions in decreasing order. See examples in
<code>VariableSelection</code>.

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

plot.variable_selection function

<dl><dt>x</dt>
<dd>output of <code>VariableSelection</code>.</dd>
<dt>col</dt>
<dd>vector of colours by stable selection status.</dd>
<dt>col.axis</dt>
<dd>optional vector of label colours by stable selection status.</dd>
<dt>col.thr</dt>
<dd>threshold colour.</dd>
<dt>lty.thr</dt>
<dd>threshold line type as <code>lty</code> in
<code><a href="/link/par?package=sharp&version=1.4.7" data-mini-rdoc="sharp::par">par</a></code>.</dd>
<dt>n_predictors</dt>
<dd>number of predictors to display.</dd>
<dt>...</dt>
<dd>additional plotting arguments (see <code><a href="/link/par?package=sharp&version=1.4.7" data-mini-rdoc="sharp::par">par</a></code>).</dd></dl>

Arguments

Plot of selection proportions — plot.variable_selection

<dl>

<dt>x</dt>
<dd>output of <code>VariableSelection</code>.</dd>


<dt>col</dt>
<dd>vector of colours by stable selection status.</dd>


<dt>col.axis</dt>
<dd>optional vector of label colours by stable selection status.</dd>


<dt>col.thr</dt>
<dd>threshold colour.</dd>


<dt>lty.thr</dt>
<dd>threshold line type as <code>lty</code> in
<code><a href='https://rdrr.io/r/graphics/par.html'>par</a></code>.</dd>


<dt>n_predictors</dt>
<dd>number of predictors to display.</dd>


<dt>...</dt>
<dd>additional plotting arguments (see <code><a href='https://rdrr.io/r/graphics/par.html'>par</a></code>).</dd>

</dl>

plot.variable_selection: Plot of selection proportions

Description

Usage

Value

Arguments

See Also