Predictive multivariate modelling for metabolomics. Types: Classification and regression. Methods: Partial Least Squares, Random Forest ans Elastic Net Data structures: Paired and unpaired Validation: repeated double cross-validation (Westerhuis et al. (2008)<doi:10.1007/s11306-007-0099-6>, Filzmoser et al. (2009)<doi:10.1002/cem.1225>) Variable selection: Performed internally, through tuning in the inner cross-validation loop.
Version: 0.1.0 Depends: R (≥ 3.5.0) Imports: stats, graphics, randomForest, ranger, pROC, doParallel, foreach, caret, glmnet, splines, dplyr, psych, magrittr, mgcv, grDevices, parallel Suggests: testthat (≥ 3.0.0) Published: 2024-09-16 DOI: 10.32614/CRAN.package.MUVR2 Author: Carl Brunius [aut], Yingxiao Yan [aut, cre] Maintainer: Yingxiao Yan <yingxiao at chalmers.se> BugReports: https://github.com/MetaboComp/MUVR2/issues License: GPL-3 URL: https://github.com/MetaboComp/MUVR2 NeedsCompilation: no Materials: README CRAN checks: MUVR2 results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=MUVR2 to link to this page.
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