generate_scrcoef_marglik

Generate screening coefficient based on marginal likelihood in univariate GLMs

internal

A flexible framework combining
variable screening and random projection techniques for fitting ensembles of
predictive generalized linear models to high-dimensional data.
Designed for extensibility, the package implements
key techniques as S3 classes with user-friendly constructors,
enabling easy integration and development of new procedures for
high-dimensional applications. For more details see
Parzer et al (2024a) <doi:10.48550/arXiv.2312.00130> and
Parzer et al (2024b) <doi:10.48550/arXiv.2410.00971>.

Laura Vana-Gür

spareg

Sparse Projected Averaged Regression

Roman Parzer

Peter Filzmoser

generate_scrcoef_marglik function

<dl><dt>y</dt>
<dd>vector of responses</dd>
<dt>x</dt>
<dd>matrix of predictors</dd>
<dt>object</dt>
<dd><code>'screencoef'</code> object</dd></dl>

Arguments

Generate screening coefficient based  on marginal likelihood in univariate GLMs — generate_scrcoef_marglik

<dl>

<dt>y</dt>
<dd>vector of responses</dd>


<dt>x</dt>
<dd>matrix of predictors</dd>


<dt>object</dt>
<dd><code>'screencoef'</code> object</dd>

</dl>

generate_scrcoef_marglik: Generate screening coefficient based on marginal likelihood in univariate GLMs

Description

Usage

Value

Arguments