BinomialProbabilities

Computes the probabilities of observing each category of selection
proportions under the assumption of a uniform selection procedure.

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

BinomialProbabilities function

<dl><dt>q</dt>
<dd>average number of features selected by the underlying algorithm.</dd>
<dt>N</dt>
<dd>total number of features.</dd>
<dt>pi</dt>
<dd>threshold in selection proportions. If n_cat=3, these values must
be &gt;0.5 and &lt;1. If n_cat=2, these values must be &gt;0 and &lt;1.</dd>
<dt>K</dt>
<dd>number of resampling iterations.</dd>
<dt>n_cat</dt>
<dd>computation options for the stability score. Default is
<code>NULL</code> to use the score based on a z test. Other possible values are 2
or 3 to use the score based on the negative log-likelihood.</dd></dl>

Arguments

Binomial probabilities for stability score — BinomialProbabilities

<dl>

<dt>q</dt>
<dd>average number of features selected by the underlying algorithm.</dd>


<dt>N</dt>
<dd>total number of features.</dd>


<dt>pi</dt>
<dd>threshold in selection proportions. If n_cat=3, these values must
be &gt;0.5 and &lt;1. If n_cat=2, these values must be &gt;0 and &lt;1.</dd>


<dt>K</dt>
<dd>number of resampling iterations.</dd>


<dt>n_cat</dt>
<dd>computation options for the stability score. Default is
<code>NULL</code> to use the score based on a z test. Other possible values are 2
or 3 to use the score based on the negative log-likelihood.</dd>

</dl>

BinomialProbabilities: Binomial probabilities for stability score

Description

Usage

Value

Arguments