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