buildPredmat.default

These are not intended for use by users. Constructs a prediction matrix for cross-validation folds, using the coefficient paths in <code>outlist</code>. Inspired by internal functions in the glmnet package.

Implements 'glmnet'-style complex-valued lasso and
complex-valued graphical lasso using a 'pathwise' coordinate descent
algorithm for complex-valued parameters. The package provides
supporting tools for estimation, simulation, and prediction. See Deb
(2024) <doi:10.48550/ArXiv.2401.11128> for the algorithm description.

Younghoon Kim

cxreg

Complex-Valued Lasso and Complex-Valued Graphical Lasso

Navonil Deb

Sumanta Basu

buildPredmat.default function

<dl><dt>outlist</dt>
<dd>A list of fitted models.</dd>
<dt>lambda</dt>
<dd>A vector of penalty values.</dd>
<dt>x</dt>
<dd>A predictor matrix.</dd>
<dt>foldid</dt>
<dd>Fold identifiers.</dd>
<dt>alignment</dt>
<dd>Alignment method (not used).</dd>
<dt>...</dt>
<dd>Other arguments</dd></dl>

Arguments

Build Prediction Matrix (Default Method) — buildPredmat.default

<dl>

<dt>outlist</dt>
<dd>A list of fitted models.</dd>


<dt>lambda</dt>
<dd>A vector of penalty values.</dd>


<dt>x</dt>
<dd>A predictor matrix.</dd>


<dt>foldid</dt>
<dd>Fold identifiers.</dd>


<dt>alignment</dt>
<dd>Alignment method (not used).</dd>


<dt>...</dt>
<dd>Other arguments</dd>

</dl>

buildPredmat.default: Build Prediction Matrix (Default Method)

Description

Usage

Value

Arguments