all_equal               Function to check whether all elements in a
                        numeric vector are equal within some tolerance
check_arguments         Checks the arguments passed to the error rate
                        estimator functions.
cov_autocorrelation     Constructs a p-dimensional covariance matrix
                        with an autocorrelation (autoregressive)
                        structure.
cov_block_autocorrelation
                        Generates a p-dimensional block-diagonal
                        covariance matrix with autocorrelated blocks.
cov_intraclass          Constructs a p-dimensional intraclass
                        covariance matrix.
cv_partition            Partitions data for cross-validation.
errorest                Wrapper function to estimate the error rate of
                        a classifier
errorest_632            Calculates the .632 Error Rate for a specified
                        classifier given a data set.
errorest_632plus        Calculates the .632+ Error Rate for a specified
                        classifier given a data set.
errorest_apparent       Calculates the Apparent Error Rate for a
                        specified classifier given a data set.
errorest_bcv            Calculates the Bootstrap Cross-Validation (BCV)
                        Error Rate Estimator for a specified classifier
                        given a data set.
errorest_boot           Calculates the Bootstrap Error Rate for a
                        specified classifier given a data set.
errorest_cv             Calculates the Cross-Validation Error Rate for
                        a specified classifier given a data set.
errorest_loo_boot       Calculates the Leave-One-Out (LOO) Bootstrap
                        Error Rate for a specified classifier given a
                        data set.
partition_data          Helper function that partitions a data set into
                        training and test data sets.
simdata                 Wrapper function to generate data from a
                        variety of data-generating families for
                        classification studies.
simdata_contaminated    Generates random variates from K multivariate
                        contaminated normal populations.
simdata_friedman        Generates data from 3 multivariate normal data
                        populations having the covariance structure
                        from Friedman (1989).
simdata_guo             Generates data from 'K' multivariate normal
                        data populations having the covariance
                        structure from Guo et al. (2007).
simdata_normal          Generates random variates from K multivariate
                        normal populations.
simdata_t               Generates random variates from K multivariate
                        Student's t populations.
simdata_uniform         Generates random variates from multivariate
                        uniform populations.
sortinghat              sortinghat
which_min               Helper function that determines which element
                        in a vector is the minimum. Ties can be broken
                        randomly or via first/last ordering.
