Bioconductor version: Release (3.15)
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 (from within R,
enter citation("pengls")
):
To install this package, start R (version "4.2") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pengls")
HTML | R Script | Vignette of the pengls package |
Reference Manual | ||
Text | NEWS |
biocViews | Regression, Software, TimeCourse, Transcriptomics |
Version | 1.2.0 |
In Bioconductor since | BioC 3.14 (R-4.1) (1 year) |
License | GPL-2 |
Depends | R (>= 4.0) |
Imports | glmnet, nlme, stats, BiocParallel |
LinkingTo | |
Suggests | knitr, rmarkdown, testthat |
SystemRequirements | |
Enhances | |
URL | |
BugReports | https://github.com/sthawinke/pengls |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | pengls_1.2.0.tar.gz |
Windows Binary | pengls_1.2.0.zip |
macOS Binary (x86_64) | pengls_1.2.0.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 |
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