matrix.standardize

Extremely efficient procedures for fitting the entire group lasso and group elastic net regularization path for GLMs, multinomial, the Cox model and multi-task Gaussian models. Similar to the R package 'glmnet' in scope of models, and in computational speed. This package provides R bindings to the C++ code underlying the corresponding Python package 'adelie'. These bindings offer a general purpose group elastic net solver,
a wide range of matrix classes that can exploit special structure
to allow large-scale inputs, and an assortment of
generalized linear model classes for fitting various types of data.
The package is an implementation of Yang, J. and Hastie, T. (2024) <doi:10.48550/arXiv.2405.08631>.

Trevor Hastie

adelie

Group Lasso and Elastic Net Solver for Generalized Linear Models

James Yang

Balasubramanian Narasimhan

matrix.standardize function

<dl><dt>mat</dt>
<dd>An <code>adelie</code> matrix.</dd>
<dt>centers</dt>
<dd>The center values. Default is to use the column means.</dd>
<dt>scales</dt>
<dd>The scale values. Default is to use the sample standard deviations.</dd>
<dt>weights</dt>
<dd>Observation weight vector, which defaults to 1/n per observation.</dd>
<dt>ddof</dt>
<dd>Degrees of freedom for standard deviations, with default 0 (1/n). The alternative is 1 leading to 1/(n-1).</dd>
<dt>n_threads</dt>
<dd>Number of threads.</dd></dl>

Arguments

James Yang, Trevor Hastie, and Balasubramanian Narasimhan Maintainer: Trevor Hastie <a href="/link/hastie%40stanford.edu?package=adelie&version=1.0.7" data-mini-rdoc="adelie::hastie@stanford.edu">hastie@stanford.edu</a>

Author

Creates a standardized matrix. — matrix.standardize

<dl>

<dt>mat</dt>
<dd>An <code>adelie</code> matrix.</dd>


<dt>centers</dt>
<dd>The center values. Default is to use the column means.</dd>


<dt>scales</dt>
<dd>The scale values. Default is to use the sample standard deviations.</dd>


<dt>weights</dt>
<dd>Observation weight vector, which defaults to 1/n per observation.</dd>


<dt>ddof</dt>
<dd>Degrees of freedom for standard deviations, with default 0 (1/n). The alternative is 1 leading to 1/(n-1).</dd>


<dt>n_threads</dt>
<dd>Number of threads.</dd>

</dl>

James Yang, Trevor Hastie, and Balasubramanian Narasimhan Maintainer: Trevor Hastie <a href='mailto:hastie@stanford.edu'>hastie@stanford.edu</a>

matrix.standardize: Creates a standardized matrix.

Description

Usage

Value

Arguments

Author

Examples