sRDA: Sparse Redundancy Analysis

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>
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:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: sRDA_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: sRDA_1.0.0.tgz


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