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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 |
| 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-oldrel (arm64): mdw_2020.6-17.tgz, r-release (x86_64): mdw_2020.6-17.tgz, r-oldrel (x86_64): mdw_2020.6-17.tgz |
| Old sources: | mdw archive |
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