Fast Cross-Validation via Sequential Testing

The fast cross-validation via sequential testing (CVST) procedure is an improved cross-validation procedure which uses non-parametric testing coupled with sequential analysis to determine the best parameter set on linearly increasing subsets of the data. By eliminating under-performing candidates quickly and keeping promising candidates as long as possible, the method speeds up the computation while preserving the capability of a full cross-validation. Additionally to the CVST the package contains an implementation of the ordinary k-fold cross-validation with a flexible and powerful set of helper objects and methods to handle the overall model selection process. The implementations of the Cochran's Q test with permutations and the sequential testing framework of Wald are generic and can therefore also be used in other contexts.


Fast Cross-Validation via Sequential Testing

The package CVST is hosted on CRAN, so

install.packages("CVST")
library(CVST)
example(CVST)

will give you a first impression.

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Reference manual

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install.packages("CVST")

0.2-2 by Tammo Krueger, 2 years ago


Browse source code at https://github.com/cran/CVST


Authors: Tammo Krueger , Mikio Braun


Documentation:   PDF Manual  


GPL (>= 2.0) license


Depends on kernlab, Matrix


Imported by GeneralisedCovarianceMeasure.

Depended on by DRR.


See at CRAN