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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.
| Version: | 0.2-3 |
| Depends: | kernlab, Matrix |
| Published: | 2022-02-21 |
| DOI: | 10.32614/CRAN.package.CVST |
| 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 |
| Reference manual: | CVST.pdf |
| Package source: | CVST_0.2-3.tar.gz |
| Windows binaries: | r-devel: CVST_0.2-3.zip, r-release: CVST_0.2-3.zip, r-oldrel: CVST_0.2-3.zip |
| macOS binaries: | r-release (arm64): CVST_0.2-3.tgz, r-oldrel (arm64): CVST_0.2-3.tgz, r-release (x86_64): CVST_0.2-3.tgz, r-oldrel (x86_64): CVST_0.2-3.tgz |
| Old sources: | CVST archive |
| Reverse depends: | DRR |
| Reverse imports: | GeneralisedCovarianceMeasure |
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