pengls
This is the released version of pengls; for the devel version, see pengls.
Fit Penalised Generalised Least Squares models
Bioconductor version: Release (3.23)
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.
Author: Stijn Hawinkel [cre, aut] 
Maintainer: Stijn Hawinkel <stijn.hawinkel at psb.ugent.be>
citation("pengls")):Stijn Hawinkel. pengls: Fit Penalised Generalised Least Squares models. doi:10.18129/B9.bioc.pengls, R package version 1.18.0, https://bioconductor.org/packages/pengls.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("pengls")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pengls")| Vignette of the pengls package | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Regression, Software, Spatial, TimeCourse, Transcriptomics |
| Version | 1.18.0 |
| In Bioconductor since | BioC 3.14 (R-4.1) (5 years) |
| License | GPL-2 |
| Depends | R (>= 4.5.0) |
| Imports | glmnet, nlme, stats, BiocParallel |
| System Requirements | |
| URL | https://github.com/sthawinke/pengls |
| Bug Reports | https://github.com/sthawinke/pengls/issues |
See More
| Suggests | knitr, rmarkdown, testthat |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | pengls_1.18.0.tar.gz |
| Windows Binary (x86_64) | pengls_1.18.0.zip |
| macOS Binary (big-sur-x86_64) | pengls_1.18.0.tgz |
| macOS Binary (sonoma-arm64) | pengls_1.18.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/pengls |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/pengls |
| Package Short Url | https://bioconductor.org/packages/pengls/ |
| Package Downloads Report | Download Stats |