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pengls

Fit Penalised Generalised Least Squares models

Bioconductor version: 3.24 · Package version: 1.19.0

Combine generalised least squares methodology from the nlme package for dealing with autocorrelation with penalised least squares methods from the glmnet package to deal with high dimensionality. This pengls packages glues them together through an iterative loop. The resulting method is applicable to high dimensional datasets that exhibit autocorrelation, such as spatial or temporal data.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("pengls")

Details

MaintainerStijn Hawinkel <stijn.hawinkel@psb.ugent.be>
AuthorStijn Hawinkel [cre, aut] (ORCID: <https://orcid.org/0000-0002-4501-5180>)
LicenseGPL-2
URLhttps://github.com/sthawinke/pengls
Bug Reportshttps://github.com/sthawinke/pengls/issues
Downloads rank285
Source branchdevel
biocViewsRegression, Software, Spatial, TimeCourse, Transcriptomics

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagepengls_1.19.0.tar.gz
Windows binary (x86_64)pengls_1.19.0.zip
macOS binary (arm64)pengls_1.19.0.tgz
macOS binary (x86_64)pengls_1.19.0.tgz
Dependencies

Depends: R (>= 4.5.0)

Imports: glmnet, nlme, stats, BiocParallel

Suggests: knitr, rmarkdown, testthat