pengls
Fit Penalised Generalised Least Squares models
Bioconductor version: 3.24 · Package version: 1.19.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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
| Maintainer | Stijn Hawinkel <stijn.hawinkel@psb.ugent.be> |
| Author | Stijn Hawinkel [cre, aut] (ORCID: <https://orcid.org/0000-0002-4501-5180>) |
| License | GPL-2 |
| URL | https://github.com/sthawinke/pengls |
| Bug Reports | https://github.com/sthawinke/pengls/issues |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | Regression, Software, Spatial, TimeCourse, Transcriptomics |
| Package Short Url | https://bioconductor.org/packages/pengls/ |
Citation
From within R, enter citation("pengls"):
Stijn Hawinkel. pengls: Fit Penalised Generalised Least Squares models. doi:10.18129/B9.bioc.pengls, R package version 1.19.0, https://bioconductor.org/packages/pengls.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | pengls_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 |