DirichletRF: "Dirichlet Random Forest"

Implementation of the Dirichlet Random Forest algorithm for compositional response data. Supports maximum likelihood estimation ('MLE') and method-of-moments ('MOM') parameter estimation for the Dirichlet distribution. Provides two prediction strategies; averaging-based predictions (average of responses within terminal nodes) and parameter-based predictions (expected value derived from the estimated Dirichlet parameters within terminal nodes). For more details see Masoumifard, van der Westhuizen, and Gardner-Lubbe (2026, ISBN:9781032903910).

Version: 0.1.0
Imports: Rcpp (≥ 1.0.0), parallel
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0)
Published: 2026-03-23
DOI: 10.32614/CRAN.package.DirichletRF (may not be active yet)
Author: Khaled Masoumifard ORCID iD [aut, cre], Stephan van der Westhuizen ORCID iD [aut], Sugnet Lubbe ORCID iD [aut]
Maintainer: Khaled Masoumifard <masoumifardk at yahoo.com>
License: GPL-3
NeedsCompilation: yes
CRAN checks: DirichletRF results

Documentation:

Reference manual: DirichletRF.html , DirichletRF.pdf

Downloads:

Package source: DirichletRF_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): DirichletRF_0.1.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): DirichletRF_0.1.0.tgz, r-oldrel (x86_64): DirichletRF_0.1.0.tgz

Linking:

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