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, 39(9): btad545. <doi:10.1093/bioinformatics/btad545>.
| Version: | 1.2 |
| Depends: | R (≥ 4.0) |
| Imports: | Rfast, stats |
| Suggests: | Rfast2 |
| Published: | 2024-12-23 |
| DOI: | 10.32614/CRAN.package.epilogi |
| 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 |
| Reference manual: | epilogi.pdf |
| Package source: | epilogi_1.2.tar.gz |
| Windows binaries: | r-devel: epilogi_1.2.zip, r-release: epilogi_1.2.zip, r-oldrel: epilogi_1.2.zip |
| macOS binaries: | r-devel (arm64): epilogi_1.2.tgz, r-release (arm64): epilogi_1.2.tgz, r-oldrel (arm64): epilogi_1.2.tgz, r-devel (x86_64): epilogi_1.2.tgz, r-release (x86_64): epilogi_1.2.tgz, r-oldrel (x86_64): epilogi_1.2.tgz |
| Old sources: | epilogi archive |
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