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Implements the high-dimensional two-sample test proposed by Zhang (2019) <http://hdl.handle.net/2097/40235>. It also implements the test proposed by Srivastava, Katayama, and Kano (2013) <doi:10.1016/j.jmva.2012.08.014>. These tests are particularly suitable to high dimensional data from two populations for which the classical multivariate Hotelling's T-square test fails due to sample sizes smaller than dimensionality. In this case, the ZWL and ZWLm tests proposed by Zhang (2019) <http://hdl.handle.net/2097/40235>, referred to as zwl_test() in this package, provide a reliable and powerful test.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.1.0) |
| Imports: | stats |
| Published: | 2020-06-12 |
| DOI: | 10.32614/CRAN.package.highDmean |
| Author: | Huaiyu Zhang, Haiyan Wang |
| Maintainer: | Huaiyu Zhang <huaiyuzhang1988 at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | highDmean results |
| Reference manual: | highDmean.pdf |
| Package source: | highDmean_0.1.0.tar.gz |
| Windows binaries: | r-devel: highDmean_0.1.0.zip, r-release: highDmean_0.1.0.zip, r-oldrel: highDmean_0.1.0.zip |
| macOS binaries: | r-release (arm64): highDmean_0.1.0.tgz, r-oldrel (arm64): highDmean_0.1.0.tgz, r-release (x86_64): highDmean_0.1.0.tgz, r-oldrel (x86_64): highDmean_0.1.0.tgz |
| Reverse suggests: | highd2means |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.