rfvimptest: Sequential Permutation Testing of Random Forest Variable
Importance Measures
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>.
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