CheckDataRegression

Checks if input data formats are appropriate. For inappropriate inputs, this
function (i) fixes the data format, or (ii) stops the run and generates an
error message.

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

CheckDataRegression function

<dl><dt>xdata</dt>
<dd>matrix of predictors with observations as rows and variables as
columns.</dd>
<dt>ydata</dt>
<dd>optional vector or matrix of outcome(s). If <code>family</code> is set
to <code>"binomial"</code> or <code>"multinomial"</code>, <code>ydata</code> can be a vector
with character/numeric values or a factor.</dd>
<dt>family</dt>
<dd>type of regression model. This argument is defined as in
<code>glmnet</code>. Possible values include <code>"gaussian"</code>
(linear regression), <code>"binomial"</code> (logistic regression),
<code>"multinomial"</code> (multinomial regression), and <code>"cox"</code> (survival
analysis).</dd>
<dt>verbose</dt>
<dd>logical indicating if a loading bar and messages should be
printed.</dd></dl>

Arguments

Checking input data (regression model) — CheckDataRegression

<dl>

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


<dt>ydata</dt>
<dd>optional vector or matrix of outcome(s). If <code>family</code> is set
to <code>"binomial"</code> or <code>"multinomial"</code>, <code>ydata</code> can be a vector
with character/numeric values or a factor.</dd>


<dt>family</dt>
<dd>type of regression model. This argument is defined as in
<code>glmnet</code>. Possible values include <code>"gaussian"</code>
(linear regression), <code>"binomial"</code> (logistic regression),
<code>"multinomial"</code> (multinomial regression), and <code>"cox"</code> (survival
analysis).</dd>


<dt>verbose</dt>
<dd>logical indicating if a loading bar and messages should be
printed.</dd>

</dl>

CheckDataRegression: Checking input data (regression model)

Description

Usage

Arguments