Package: PRTree
Type: Package
Date: 2026-07-13
Title: Probabilistic Regression Trees
Version: 1.1.0
Authors@R: c(
    person("Taiane Schaedler", "Prass",
           email = "taianeprass@gmail.com",
           role = c("aut", "ths", "cre"),
           comment = c(ORCID = "0000-0003-3136-909X")),
    person("Alisson Silva", "Neimaier",
           email = "alissonneimaier@hotmail.com",
           role = c("aut"),
           comment = c(ORCID = "0000-0002-7524-0776"))
  )
Depends: R (>= 4.3.0)
Suggests: ggplot2
Imports: tidyr (>= 1.3.0), gridExtra (>= 2.3), stats, grDevices, utils,
        tidyselect, graphics, rlang
Description: 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>.    
License: GPL (>= 3)
Encoding: UTF-8
NeedsCompilation: yes
Collate: 'prtree.R' 'prtree_control.R' 'prtree_control_utils.R'
        'prtree_cv.R' 'prtree_cv_methods.R' 'prtree_rules.R'
        'prtree_defaults.R' 'prtree_grid_expansion.R' 'prtree_main.R'
        'prtree_main_methods.R' 'prtree_messages.R' 'prtree_predict.R'
        'prtree_split.R' 'prtree_validation.R'
Config/roxygen2/version: 8.0.0
RoxygenNote: 7.3.3
Packaged: 2026-07-13 20:09:13 UTC; Taiane
Author: Taiane Schaedler Prass [aut, ths, cre] (ORCID:
    <https://orcid.org/0000-0003-3136-909X>),
  Alisson Silva Neimaier [aut] (ORCID:
    <https://orcid.org/0000-0002-7524-0776>)
Maintainer: Taiane Schaedler Prass <taianeprass@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-13 20:30:10 UTC
