gomp: The gamma-OMP Feature Selection Algorithm

The gamma-Orthogonal Matching Pursuit (gamma-OMP) is a recently suggested modification of the OMP feature selection algorithm for a wide range of response variables. The package offers many alternative regression models, such linear, robust, survival, multivariate etc., including k-fold cross-validation. References: Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2018). "Efficient feature selection on gene expression data: Which algorithm to use?" BioRxiv. <doi:10.1101/431734>. Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2022). "The gamma-OMP algorithm for feature selection with application to gene expression data". IEEE/ACM Transactions on Computational Biology and Bioinformatics 19(2): 1214–1224. <doi:10.1109/TCBB.2020.3029952>.

Version:	1.0
Depends:	R (≥ 4.0)
Imports:	doParallel, foreach, Hmisc, MASS, nnet, ordinal, parallel, quantreg, Rfast, Rfast2, stats, survival
Suggests:	dcorVS
Published:	2025-01-20
DOI:	10.32614/CRAN.package.gomp
Author:	Michail Tsagris [aut, cre]
Maintainer:	Michail Tsagris <mtsagris at uoc.gr>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	gomp results

Documentation:

Reference manual:

gomp.pdf

Downloads:

Package source:	gomp_1.0.tar.gz
Windows binaries:	r-devel: gomp_1.0.zip, r-release: gomp_1.0.zip, r-oldrel: gomp_1.0.zip
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): gomp_1.0.tgz, r-oldrel (x86_64): not available

Linking:

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