Multivariate Methods with Unbiased Variable Selection R package MUVR2 version 0.1.0 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. Software 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) Yingxiao Yan <yingxiao@chalmers.se> Comprehensive R Archive Network (CRAN) Carl Brunius [aut], Yingxiao Yan [aut, cre] GPL-3 2024-09-16 application/tgz https://CRAN.R-project.org/package=MUVR2 doi:10.32614/CRAN.package.MUVR2