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Sparse redundancy analysis for high dimensional (biomedical) data. Directional multivariate analysis to express the maximum variance in the predicted data set by a linear combination of variables of the predictive data set. Implemented in a partial least squares framework, for more details see Csala et al. (2017) <doi:10.1093/bioinformatics/btx374>.
| Version: | 1.0.0 |
| Depends: | R (≥ 2.7), Matrix, doParallel, elasticnet, foreach, mvtnorm |
| Published: | 2017-12-14 |
| Author: | Attila Csala [aut, cre], Koos Zwinderman [ctb] |
| Maintainer: | Attila Csala <a at csala.me> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | sRDA results |
| Reference manual: | sRDA.pdf |
| Package source: | sRDA_1.0.0.tar.gz |
| Windows binaries: | r-devel: sRDA_1.0.0.zip, r-release: sRDA_1.0.0.zip, r-oldrel: sRDA_1.0.0.zip |
| macOS binaries: | r-release (arm64): sRDA_1.0.0.tgz, r-oldrel (arm64): sRDA_1.0.0.tgz, r-release (x86_64): sRDA_1.0.0.tgz, r-oldrel (x86_64): sRDA_1.0.0.tgz |
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