Package: highDmean 0.1.0
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.
Authors:
highDmean_0.1.0.tar.gz
highDmean_0.1.0.zip(r-4.5)highDmean_0.1.0.zip(r-4.4)highDmean_0.1.0.zip(r-4.3)
highDmean_0.1.0.tgz(r-4.4-any)highDmean_0.1.0.tgz(r-4.3-any)
highDmean_0.1.0.tar.gz(r-4.5-noble)highDmean_0.1.0.tar.gz(r-4.4-noble)
highDmean_0.1.0.tgz(r-4.4-emscripten)highDmean_0.1.0.tgz(r-4.3-emscripten)
highDmean.pdf |highDmean.html✨
highDmean/json (API)
NEWS
| # Install 'highDmean' in R: |
| install.packages('highDmean', repos = c('https://huaiyuzhang.r-universe.dev', 'https://cloud.r-project.org')) |
- GO_example - An example of GO term data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:4c817fbddb. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 12 2024 |
| R-4.5-win | OK | Nov 12 2024 |
| R-4.5-linux | OK | Nov 12 2024 |
| R-4.4-win | OK | Nov 12 2024 |
| R-4.4-mac | OK | Nov 12 2024 |
| R-4.3-win | OK | Nov 12 2024 |
| R-4.3-mac | OK | Nov 12 2024 |
Exports:buildDatargammashiftSKK_simSKK_testzwl_simzwl_test
Dependencies:
