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LASSO (Least Absolute Shrinkage and Selection Operator) regression for compositional responses with and without zero values present and continuous predictors. The choice of the penalty parameter, lambda, takes place using K-fold cross-validation. Two relevant papers are Li Z. et al. (2018) <doi:10.1007/s12561-018-9219-2> and Alenazi A.A. (2022) <doi:10.18187/pjsor.v18i4.3969>.
| Version: | 1.0 |
| Depends: | R (≥ 4.0) |
| Imports: | Compositional, glmnet, Rfast, stats |
| Suggests: | Rfast2 |
| Published: | 2026-11-03 |
| DOI: | 10.32614/CRAN.package.CompositionalLASSO |
| 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: | CompositionalLASSO results |
| Reference manual: | CompositionalLASSO.html , CompositionalLASSO.pdf |
| Package source: | CompositionalLASSO_1.0.tar.gz |
| Windows binaries: | r-devel: CompositionalLASSO_1.0.zip, r-release: CompositionalLASSO_1.0.zip, r-oldrel: CompositionalLASSO_1.0.zip |
| macOS binaries: | r-release (arm64): CompositionalLASSO_1.0.tgz, r-oldrel (arm64): CompositionalLASSO_1.0.tgz, r-release (x86_64): CompositionalLASSO_1.0.tgz, r-oldrel (x86_64): CompositionalLASSO_1.0.tgz |
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