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
NeedsCompilation: no
Packaged: 2025-05-08 16:35:27 UTC; hornung
Author: Alexander Hapfelmeier [aut],
  Roman Hornung [aut, cre]
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>
Repository: CRAN
Date/Publication: 2025-05-08 22:10:02 UTC
Built: R 4.6.0; ; 2026-04-29 07:12:09 UTC; unix
