count_variables         count the number of times each variable is used
                        in a ranger random forest
determine.C             determine.C
determine_cutoff        evaluate a measure that can be used to
                        determining a significance level for the Mean
                        Decrease in Impurity measure returned by a
                        Random Forest model
f.fit                   fit a spline to the histogram of imp
fit.to.data.set         fit.to.data.set
fit.to.data.set.wrapper
                        fit.to.data.set.wrapper
imp20000                20000 importance values
local.fdr               local fdr
my.dsn                  my.dsn
my.test1fun             my.test1fun
my_PIMP                 my_PIMP based on the PIMP function from the
                        vita package. ‘PIMP’ implements the test
                        approach of Altmann et al. (2010) for the
                        permutation variable importance measure
                        ‘VarImp’ returned by the randomForest package
                        (Liaw and Wiener (2002)) for classification and
                        regression.
my_ranger_PIMP          my_ranger_PIMP based on the PIMP function from
                        the vita package. ‘PIMP’ implements the test
                        approach of Altmann et al. (2010) for the
                        permutation variable importance measure
                        ‘VarImp’ returned by the randomForest package
                        (Liaw and Wiener (2002)) for classification and
                        regression.
plotQ                   plotQ
propTrueNullByLocalFDR
                        propTrueNullByLocalFDR
run.it.importances      run.it.importances
significant.genes       significant.genes
