mdw: Maximum Diversity Weighting

Dimension-reduction methods aim at defining a score that maximizes signal diversity. Three approaches, tree weight, maximum entropy weights, and maximum variance weights are provided. These methods are described in He and Fong (2019) <doi:10.1002/sim.8212>.

Version: 2020.6-17
Depends: R (≥ 3.5.0)
Imports: kyotil, MASS, Matrix
Suggests: R.rsp, RUnit, Rmosek, mvtnorm, MethylCapSig, gtools
Published: 2020-06-18
Author: Zonglin He [aut], Youyi Fong [cre]
Maintainer: Youyi Fong <youyifong at gmail.com>
License: GPL-2
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: mdw results

Downloads:

Reference manual: mdw.pdf
Vignettes: Maximum Diversity Weighting
Package source: mdw_2020.6-17.tar.gz
Windows binaries: r-devel: mdw_2020.6-17.zip, r-release: mdw_2020.6-17.zip, r-oldrel: mdw_2020.6-17.zip
macOS binaries: r-release (arm64): mdw_2020.6-17.tgz, r-release (x86_64): mdw_2020.6-17.tgz, r-oldrel: mdw_2020.6-17.tgz
Old sources: mdw archive

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