boostPM: Unsupervised Tree Boosting for Learning Probability Distributions

Implements the unsupervised tree boosting method for learning probability distributions introduced by Awaya and Ma (2024). Provides model fitting, density evaluation, simulation, and diagnostic methods.

Version: 0.1.0
Imports: graphics, Rcpp (≥ 1.0.7), stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0), knitr (≥ 1.43), rmarkdown (≥ 2.20)
Published: 2026-07-26
DOI: 10.32614/CRAN.package.boostPM (may not be active yet)
Author: Naoki Awaya [aut, cre]
Maintainer: Naoki Awaya <nawaya at waseda.jp>
BugReports: https://github.com/nawaya040/boostPM-cran/issues
License: MIT + file LICENSE
URL: https://github.com/nawaya040/boostPM-cran
NeedsCompilation: yes
Citation: boostPM citation info
Materials: README, NEWS
CRAN checks: boostPM results

Documentation:

Reference manual: boostPM.html , boostPM.pdf
Vignettes: Introduction to boostPM (source, R code)

Downloads:

Package source: boostPM_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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