highDmean
Testing Two-Sample Mean in High Dimension
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.
- Version0.1.0
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release06/12/2020
Documentation
Team
Huaiyu Zhang
Haiyan Wang
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Last 30 days
This package has been downloaded 143 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
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Last 365 days
This package has been downloaded 2,117 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jul 21, 2024 with 67 downloads.
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Dependencies
- Reverse Suggests1 package