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: | 2024.8-1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | kyotil,MASS,Matrix |
| Suggests: | R.rsp,RUnit,Rmosek,mvtnorm,gtools |
| Published: | 2024-07-31 |
| DOI: | 10.32614/CRAN.package.mdw |
| 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.html ,mdw.pdf |
| Vignettes: | Tutorials for the R package mdw (source) |
| Package source: | mdw_2024.8-1.tar.gz |
| Windows binaries: | r-devel:mdw_2024.8-1.zip, r-release:mdw_2024.8-1.zip, r-oldrel:mdw_2024.8-1.zip |
| macOS binaries: | r-release (arm64):mdw_2024.8-1.tgz, r-oldrel (arm64):mdw_2024.8-1.tgz, r-release (x86_64):mdw_2024.8-1.tgz, r-oldrel (x86_64):mdw_2024.8-1.tgz |
| Old sources: | mdw archive |
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