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Two-step modeling with separation of sources of variation through analysis of variance and subsequent multivariate modeling through a range of unsupervised and supervised statistical methods. Separation can focus on removal of interfering effects or isolation of effects of interest. EF Mosleth et al. (2021) <doi:10.1038/s41598-021-82388-w> and EF Mosleth et al. (2020) <doi:10.1016/B978-0-12-409547-2.14882-6>.
Version: | 1.2.1 |
Depends: | R (≥ 3.5.0) |
Imports: | ggplot2, scales, gridExtra, glmnet, pls, plsVarSel, mixlm, HDANOVA, lme4, pracma, neuralnet |
Published: | 2025-06-27 |
Author: | Kristian Hovde Liland [aut, cre], Ellen Færgestad Mosleth [ctb] |
Maintainer: | Kristian Hovde Liland <kristian.liland at nmbu.no> |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | gemR results |
Reference manual: | gemR.pdf |
Package source: | gemR_1.2.1.tar.gz |
Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): gemR_1.2.1.tgz, r-oldrel (x86_64): gemR_1.2.1.tgz |
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These binaries (installable software) and packages are in development.
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