epilogi: The 'epilogi' Variable Selection Algorithm for Continuous Data

The 'epilogi' variable selection algorithm is implemented for the case of continuous response and predictor variables. The relevant paper is: Lakiotaki K., Papadovasilakis Z., Lagani V., Fafalios S., Charonyktakis P., Tsagris M. and Tsamardinos I. (2023). "Automated machine learning for Genome Wide Association Studies". Bioinformatics. <doi:10.1002/sim.4780120902>.

Version: 1.0
Depends: R (≥ 4.0)
Imports: Rfast, stats
Published: 2023-10-01
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: epilogi results

Documentation:

Reference manual: epilogi.pdf

Downloads:

Package source: epilogi_1.0.tar.gz
Windows binaries: r-prerel: epilogi_1.0.zip, r-release: epilogi_1.0.zip, r-oldrel: epilogi_1.0.zip
macOS binaries: r-prerel (arm64): epilogi_1.0.tgz, r-release (arm64): epilogi_1.0.tgz, r-oldrel (arm64): epilogi_1.0.tgz, r-prerel (x86_64): epilogi_1.0.tgz, r-release (x86_64): epilogi_1.0.tgz

Linking:

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