CVST: Fast Cross-Validation via Sequential Testing

This package implements the fast cross-validation via sequential testing (CVST) procedure. CVST 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 underperforming 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.

Version: 0.2-1
Depends: kernlab, Matrix
Published: 2013-12-10
Author: Tammo Krueger, Mikio Braun
Maintainer: Tammo Krueger <tammokrueger at googlemail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation: no
Materials: README
CRAN checks: CVST results

Downloads:

Reference manual: CVST.pdf
Package source: CVST_0.2-1.tar.gz
Windows binaries: r-devel: CVST_0.2-1.zip, r-release: CVST_0.2-1.zip, r-oldrel: CVST_0.2-1.zip
OS X Snow Leopard binaries: r-release: CVST_0.2-1.tgz, r-oldrel: CVST_0.2-1.tgz
OS X Mavericks binaries: r-release: CVST_0.2-1.tgz
Old sources: CVST archive