Non linear regression with compositional responses and Euclidean predictors is performed. The compositional data are first transformed using the additive log-ratio transformation, and then the multivariate random forest of Rahman R., Otridge J. and Pal R. (2017), <doi:10.1093/bioinformatics/btw765>, is applied.
| Version: | 1.0 |
| Depends: | R (≥ 4.0) |
| Imports: | Compositional, doParallel, foreach, MultivariateRandomForest, Rfast, stats |
| Published: | 2024-10-02 |
| DOI: | 10.32614/CRAN.package.CompositionalRF |
| 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: | CompositionalRF results |
| Reference manual: | CompositionalRF.pdf |
| Package source: | CompositionalRF_1.0.tar.gz |
| Windows binaries: | r-devel: CompositionalRF_1.0.zip, r-release: CompositionalRF_1.0.zip, r-oldrel: CompositionalRF_1.0.zip |
| macOS binaries: | r-release (arm64): CompositionalRF_1.0.tgz, r-oldrel (arm64): CompositionalRF_1.0.tgz, r-release (x86_64): CompositionalRF_1.0.tgz, r-oldrel (x86_64): CompositionalRF_1.0.tgz |
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