Package: literanger
Title: Fast Serializable Random Forests Based on 'ranger'
Version: 0.2.0
Authors@R: 
    c(person("Stephen", "Wade",
             email="stephematician@gmail.com",
             comment=c(ORCID="0000-0002-2573-9683"),
             role=c("aut", "cre")),
      person("Marvin N", "Wright",
             email="web@wrig.de",
             role=c("ctb")))
Description: An updated implementation of R package 'ranger' by Wright et al,
    (2017) <doi:10.18637/jss.v077.i01> for training and predicting from random
    forests, particularly suited to high-dimensional data, and for embedding in
    'Multiple Imputation by Chained Equations' (MICE) by van Buuren (2007)
    <doi:10.1177/0962280206074463>. Ensembles of classification and regression
    trees are currently supported. Sparse data of class 'dgCMatrix' (R package
    'Matrix') can be directly analyzed. Conventional bagged predictions are
    available alongside an efficient prediction for MICE via the algorithm
    proposed by Doove et al (2014) <doi:10.1016/j.csda.2013.10.025>. Trained
    forests can be written to and read from storage. Survival and probability
    forests are not supported in the update, nor is data of class 'gwaa.data'
    (R package 'GenABEL'); use the original 'ranger' package for these analyses.
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
BugReports: https://gitlab.com/stephematician/literanger/-/issues
URL: https://gitlab.com/stephematician/literanger
Suggests: Matrix (>= 1.5.3), testthat (>= 3.0.0), tibble (>= 3.2.1)
Imports: stats
LinkingTo: cpp11 (>= 0.4.7), Rcereal (>= 1.3.2)
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2025-07-13 07:11:20 UTC; stephematician
Author: Stephen Wade [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-2573-9683>),
  Marvin N Wright [ctb]
Maintainer: Stephen Wade <stephematician@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-13 07:30:02 UTC
Built: R 4.3.3; aarch64-apple-darwin20; 2025-07-14 21:55:09 UTC; unix
Archs: literanger.so.dSYM
