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Sparse regression with paired covariates

The paired lasso is designed for situations where each covariate in one set forms a pair with a covariate in the other set (i.e., settings with a one-to-one correspondence between two covariate sets).

Installation

Install the current release from CRAN, or the latest development version from GitHub:

install.packages("palasso")
#install.packages("remotes")
remotes::install_github("rauschenberger/palasso")

Optionally, install ashr and CorShrink for the correlation shrinkage:

remotes::install_github("stephens999/ashr")
remotes::install_github("kkdey/CorShrink")

Reference

Armin Rauschenberger , Iuliana Ciocănea-Teodorescu , Marianne A. Jonker , Renée X. Menezes , and Mark A. van de Wiel (2020). "Sparse classification with paired covariates". Advances in Data Analysis and Classification 14:571-588. doi: 10.1007/s11634-019-00375-6.

Disclaimer

The R package palasso implements sparse regression with paired covariates (Rauschenberger et al., 2020).

Copyright © 2017 Armin Rauschenberger, Department of Epidemiology and Biostatistics, Amsterdam UMC, VU University Amsterdam, Amsterdam, The Netherlands

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

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Install

install.packages('palasso')

Monthly Downloads

270

Version

1.0.0

License

GPL-3

Issues

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Stars

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Maintainer

Armin Rauschenberger

Last Published

September 26th, 2024

Functions in palasso (1.0.0)

.folds

Cross-validation folds
.args

Arguments
.extract

Extraction
.cv

Cross-validation
.fit

Model bag
arguments

Arguments for "palasso"
.combine

Combining p-values
.dims

Dimensionality
.weight

Weighting schemes
.cor

Correlation
other

Analysis functions for manuscript
palasso

Paired lasso
.loss

Cross-validation loss
methods

Methods for class "palasso"
plots

Plot functions for manuscript