Package: PRTree 1.0.3

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