conv.factor             Convert variables to factors
gen.mcar                Generate missing (completely at random) cells
                        in a data set
imp.rfemp               Perform multiple imputation using the empirical
                        error distributions and predicted probabilities
                        of random forests
imp.rfnode.cond         Perform multiple imputation based on the
                        conditional distribution formed by prediction
                        nodes of random forests
imp.rfnode.prox         Perform multiple imputation based on the
                        conditional distribution formed using node
                        proximity
mice.impute.rfemp       Univariate sampler function for mixed types of
                        variables for prediction-based imputation,
                        using empirical distribution of out-of-bag
                        prediction errors and predicted probabilities
                        of random forests
mice.impute.rfnode      Univariate sampler function for mixed types of
                        variables for node-based imputation, using
                        predicting nodes of random forests
mice.impute.rfpred.cate
                        Univariate sampler function for categorical
                        variables for prediction-based imputation,
                        using predicted probabilities of random forest
mice.impute.rfpred.emp
                        Univariate sampler function for continuous
                        variables using the empirical error
                        distributions
mice.impute.rfpred.norm
                        Univariate sampler function for continuous
                        variables for prediction-based imputation,
                        assuming normality for prediction errors of
                        random forest
query.rf.pred.idx       Identify corresponding observations indexes
                        under the terminal nodes for a random forest
                        model by 'ranger'
query.rf.pred.val       Identify corresponding observed values for the
                        response variable under the terminal nodes for
                        a random forest model by 'ranger'
rangerCallerSafe        Remove unnecessary arguments for 'ranger'
                        function
reg.ests                Get regression estimates for pooled object
