Package: rfvimptest
Type: Package
Title: Sequential Permutation Testing of Random Forest Variable
        Importance Measures
Version: 0.1.4
Date: 2025-05-08
Authors@R: c(person("Alexander", "Hapfelmeier", role = c("aut"),
                      email = "Alexander.Hapfelmeier@mri.tum.de"),
             person("Roman", "Hornung", role = c("aut", "cre"), 
                      email = "hornung@ibe.med.uni-muenchen.de"))
Description: Sequential permutation testing for statistical
        significance of predictors in random forests and other
        prediction methods. The main function of the package is
        rfvimptest(), which allows to test for the statistical
        significance of predictors in random forests using different
        (sequential) permutation test strategies [1]. The advantage of
        sequential over conventional permutation tests is that they are
        computationally considerably less intensive, as the sequential
        procedure is stopped as soon as there is sufficient evidence
        for either the null or the alternative hypothesis. Reference:
        [1] Hapfelmeier, A., Hornung, R. & Haller, B. (2023) Efficient
        permutation testing of variable importance measures by the
        example of random forests. Computational Statistics & Data
        Analysis 181:107689, <doi:10.1016/j.csda.2022.107689>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: party, ranger, permimp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
Repository: https://romanhornung.r-universe.dev
Date/Publication: 2025-05-08 16:44:06 UTC
RemoteUrl: https://github.com/romanhornung/rfvimptest
RemoteRef: HEAD
RemoteSha: 56d8d2f1c8991f884ef6692f0d599df4fb5c401f
NeedsCompilation: no
Packaged: 2026-07-04 16:33:01 UTC; root
Author: Alexander Hapfelmeier [aut],
  Roman Hornung [aut, cre]
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>