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  "Title": "Sequential Permutation Testing of Random Forest Variable\nImportance Measures",
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  "Description": "Sequential permutation testing for statistical\nsignificance of predictors in random forests and other\nprediction methods. The main function of the package is\nrfvimptest(), which allows to test for the statistical\nsignificance of predictors in random forests using different\n(sequential) permutation test strategies [1]. The advantage of\nsequential over conventional permutation tests is that they are\ncomputationally considerably less intensive, as the sequential\nprocedure is stopped as soon as there is sufficient evidence\nfor either the null or the alternative hypothesis. Reference:\n[1] Hapfelmeier, A., Hornung, R. & Haller, B. (2023) Efficient\npermutation testing of variable importance measures by the\nexample of random forests. Computational Statistics & Data\nAnalysis 181:107689, <doi:10.1016/j.csda.2022.107689>.",
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