C2SPrInDT               Two-stage estimation for classification
Mix2SPrInDT             Two-stage estimation for
                        classification-regression mixtures
NesPrInDT               Nested 'PrInDT' with additional undersampling
                        of a factor with two unbalanced levels
OptPrInDT               Optimisation of undersampling percentages for
                        classification
PostPrInDT              Posterior analysis of conditional inference
                        trees: distribution of a specified variable in
                        the terminal nodes.
PrInDT                  The basic undersampling loop for classification
PrInDTAll               Conditional inference tree (ctree) based on all
                        observations
PrInDTAllparts          Conditional inference trees (ctrees) based on
                        consecutive parts of the full sample
PrInDTCstruc            Structured subsampling for classification
PrInDTMulab             Multiple label classification based on
                        resampling by 'PrInDT'
PrInDTMulabAll          Multiple label classification based on all
                        observations
PrInDTMulev             PrInDT analysis for a classification problem
                        with multiple classes.
PrInDTMulevAll          Conditional inference tree (ctree) for multiple
                        classes on all observations
PrInDTRstruc            Structured subsampling for regression
PrInDTreg               Regression tree resampling by the PrInDT method
PrInDTregAll            Regression tree based on all observations
R2SPrInDT               Two-stage estimation for regression
RePrInDT                Repeated 'PrInDT' for specified percentage
                        combinations
SimCPrInDT              Interdependent estimation for classification
SimMixPrInDT            Interdependent estimation for
                        classification-regression mixtures
SimRPrInDT              Interdependent estimation for regression
data_land               Landscape analysis
data_speaker            Subject pronouns and a predictor with one very
                        frequent level
data_vowel              Vowel length
data_zero               Subject pronouns
participant_zero        Participants of subject pronoun study
