Package: DirichletRF 0.1.0
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).
Authors:
DirichletRF_0.1.0.tar.gz
DirichletRF_0.1.0.zip(r-4.7-x86_64)DirichletRF_0.1.0.zip(r-4.7-arm64)DirichletRF_0.1.0.zip(r-4.6-x86_64)DirichletRF_0.1.0.zip(r-4.6-arm64)DirichletRF_0.1.0.zip(r-4.5-x86_64)
DirichletRF_0.1.0.tgz(r-4.6-x86_64)DirichletRF_0.1.0.tgz(r-4.6-arm64)DirichletRF_0.1.0.tgz(r-4.5-x86_64)DirichletRF_0.1.0.tgz(r-4.5-arm64)
DirichletRF_0.1.0.tar.gz(r-4.7-arm64)DirichletRF_0.1.0.tar.gz(r-4.7-x86_64)DirichletRF_0.1.0.tar.gz(r-4.6-arm64)DirichletRF_0.1.0.tar.gz(r-4.6-x86_64)
DirichletRF_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
DirichletRF/json (API)
| # Install 'DirichletRF' in R: |
| install.packages('DirichletRF', repos = c('https://xaleed.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/xaleed/dirichletrf/issues
Last updated from:812ce362fb. Checks:13 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 108 | ||
| linux-devel-x86_64 | NOTE | 97 | ||
| source / vignettes | OK | 225 | ||
| linux-release-arm64 | NOTE | 80 | ||
| linux-release-x86_64 | NOTE | 164 | ||
| macos-release-arm64 | NOTE | 190 | ||
| macos-release-x86_64 | NOTE | 293 | ||
| macos-oldrel-arm64 | NOTE | 174 | ||
| macos-oldrel-x86_64 | NOTE | 406 | ||
| windows-devel-arm64 | NOTE | 351 | ||
| windows-devel-x86_64 | NOTE | 131 | ||
| windows-release-arm64 | NOTE | 310 | ||
| windows-release-x86_64 | NOTE | 95 | ||
| windows-oldrel-x86_64 | NOTE | 93 | ||
| wasm-release | OK | 79 |
Exports:DirichletRFimportancepermutation_importancepredict_weightssample_conditional
Dependencies:Rcpp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| DirichletRF: Dirichlet Random Forest for Compositional Data | DirichletRF-package |
| Build a Dirichlet Random Forest for Compositional Responses | DirichletRF |
| Feature Importance for a Dirichlet Forest | importance importance.DirichletRF |
| Permutation Feature Importance for a Dirichlet Forest | permutation_importance |
| Proximity Weights for New Observations | predict_weights |
| Predict with a Dirichlet Forest | predict predict.DirichletRF |
| Custom Print Method for DirichletRF Objects | print print.DirichletRF |
| Draw Conditional Samples from a Dirichlet Forest | sample_conditional |