Package: CompositionalRF 1.0

Michail Tsagris

CompositionalRF: Multivariate Random Forest with Compositional Responses

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.

Authors:Michail Tsagris [aut, cre]

CompositionalRF_1.0.tar.gz
CompositionalRF_1.0.tar.gz(r-4.5-noble)CompositionalRF_1.0.tar.gz(r-4.4-noble)
CompositionalRF_1.0.tgz(r-4.4-emscripten)CompositionalRF_1.0.tgz(r-4.3-emscripten)
CompositionalRF.pdf |CompositionalRF.html
CompositionalRF/json (API)

# Install 'CompositionalRF' in R:
install.packages('CompositionalRF', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 155 downloads 2 exports 79 dependencies

Last updated 3 months agofrom:116700f1c5. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-linuxOKDec 02 2024

Exports:comp.rfcv.comprf

Dependencies:BHbigassertrbigparallelrbigstatsrbitbootbootstrapclasscliclustercodetoolscolorspaceCompositionalcowplotdoParallelemplikenergyfansifarverffflockforeachggplot2glmnetgluegslgtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmdamgcvminpack.lmmixturemnormtMultivariateRandomForestmunsellmvhtestsnlmennetnumDerivparallellypillarpkgconfigpsquadprogquantregR6RColorBrewerRcppRcppArmadilloRcppEigenRcppGSLRcppParallelRcppZigguratregdaRfastRfast2RhpcBLASctlrlangrmioRnanoflannRSpectrascalesshapesnSparseMsurvivaltibbleutf8vctrsviridisLitewithr