Fast Cross-Validation via Sequential Testing R package CVST version 0.2-3 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. Software Depends: kernlab,Matrix Tammo Krueger <tammokrueger@googlemail.com> Comprehensive R Archive Network (CRAN) Tammo Krueger, Mikio Braun GPL (>= 2.0) 2022-02-21 application/tgz https://CRAN.R-project.org/package=CVST doi:10.32614/CRAN.package.CVST