This package is considered a duplicate. The official version of this package is found at:https://tsprass.r-universe.dev/PRTree

Package: PRTree 1.1.0

Taiane Schaedler Prass

PRTree: Probabilistic Regression Trees

Implementation of Probabilistic Regression Trees (PRTree), providing functions for model fitting and prediction, with specific adaptations to handle missing values. The main computations are implemented in 'Fortran' for high efficiency. The package is based on the PRTree methodology described in Alkhoury et al. (2020), "Smooth and Consistent Probabilistic Regression Trees" <https://proceedings.neurips.cc/paper_files/paper/2020/file/8289889263db4a40463e3f358bb7c7a1-Paper.pdf>. Details on the treatment of missing data and implementation aspects are presented in Prass, T.S.; Neimaier, A.S.; Pumi, G. (2025), "Handling Missing Data in Probabilistic Regression Trees: Methods and Implementation in R" <doi:10.48550/arXiv.2510.03634>.

Authors:Taiane Schaedler Prass [aut, ths, cre], Alisson Silva Neimaier [aut]

PRTree_1.1.0.tar.gz
PRTree_1.1.0.zip(r-4.7-x86_64)PRTree_1.1.0.zip(r-4.7-arm64)PRTree_1.1.0.zip(r-4.6-x86_64)PRTree_1.1.0.zip(r-4.6-arm64)
PRTree_1.1.0.tar.gz(r-4.7-arm64)PRTree_1.1.0.tar.gz(r-4.7-x86_64)PRTree_1.1.0.tar.gz(r-4.6-arm64)PRTree_1.1.0.tar.gz(r-4.6-x86_64)
PRTree_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
PRTree/json (API)

# Install 'PRTree' in R:

install.packages('PRTree', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
fortran– Runtime library for GNU Fortran applications

On CRAN:

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

openblas fortran

1.70 score 3 scripts 380 downloads 7 exports 22 dependencies

Last updated from:f22feb5343. Checks:8 OK, 2 ERROR. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	117
linux-devel-x86_64	OK	123
source / vignettes	OK	207
linux-release-arm64	OK	139
linux-release-x86_64	OK	147
windows-devel-arm64	ERROR	186
windows-devel-x86_64	OK	132
windows-release-arm64	ERROR	200
windows-release-x86_64	OK	69
wasm-release	OK	130

Exports:expand_sigma_grid plot_tree pr_tree pr_tree_control pr_tree_control_cv pr_tree_cv train_test_split

Dependencies:cli cpp11 dplyr generics glue gridExtra gtable lifecycle magrittr pillar pkgconfig purrr R6 rlang stringi stringr tibble tidyr tidyselect utf8 vctrs withr

Help page	Topics
Create a grid of sigma vectors for Probabilistic Regression Trees	expand_sigma_grid
Plot a PRTree as a dendrogram with gamma and P distributions	plot_tree
Plot method for PRTree objects	plot.prtree
Plot method for PRTree Cross-Validation objects	plot.prtree.cv
Probabilistic Regression Trees (PRTrees)	pr_tree
Control parameters for PRTree	pr_tree_control
Control parameters for PRTree with optional cross-validation	pr_tree_control_cv
Cross-Validation for Probabilistic Regression Trees	pr_tree_cv
Predict from a Probabilistic Regression Tree Model	predict.prtree
Print method for idx.split objects	print.idx.split
Print method for PRTree objects	print.prtree
Print method for PRTree control objects	print.prtree.control
Print method for PRTree control objects	print.prtree.control_cv
Print method for PRTree Cross-Validation objects	print.prtree.cv
Print method for sigma grid objects	print.sigma_grid
Print method for summary of 'idx.split' objects	print.summary.idx.split
Print method for summary of PRTree objects	print.summary.prtree
Print method for summary of PRTree Cross-Validation objects	print.summary.prtree.cv
Summary method for 'idx.split' objects	summary.idx.split
Summary method for PRTree objects	summary.prtree
Summary method for PRTree Cross-Validation objects	summary.prtree.cv
Split data into training and testing sets	train_test_split

Package: PRTree 1.1.0

PRTree: Probabilistic Regression Trees

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)