Package: PRTree
Type: Package
Date: 2026-02-18
Title: Probabilistic Regression Trees
Version: 1.0.3
Authors@R: c(person(c("Alisson", "Silva"),"Neimaier",
                    email = "alissonneimaier@hotmail.com",
                    role = c("aut"),
                    comment = c(ORCID="0000-0002-7524-0776")),
						person(c("Taiane", "Schaedler"),"Prass",
                     email = "taianeprass@gmail.com",
                     role = c("aut", "ths", "cre"),
                     comment = c(ORCID="0000-0003-3136-909X")))
Depends: R (>= 4.3.0)
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
RoxygenNote: 7.3.3
Packaged: 2026-02-18 22:15:47 UTC; Taiane
Author: Alisson Silva Neimaier [aut] (ORCID:
    <https://orcid.org/0000-0002-7524-0776>),
  Taiane Schaedler Prass [aut, ths, cre] (ORCID:
    <https://orcid.org/0000-0003-3136-909X>)
Maintainer: Taiane Schaedler Prass <taianeprass@gmail.com>
Repository: CRAN
Date/Publication: 2026-02-18 22:30:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-27 00:35:46 UTC; unix
Archs: PRTree.so.dSYM
