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:Huaiyu Zhang, Haiyan Wang

highDmean_0.1.0.tar.gz
highDmean_0.1.0.zip(r-4.7)highDmean_0.1.0.zip(r-4.6)highDmean_0.1.0.zip(r-4.5)
highDmean_0.1.0.tgz(r-4.6-any)highDmean_0.1.0.tgz(r-4.5-any)
highDmean_0.1.0.tar.gz(r-4.7-any)highDmean_0.1.0.tar.gz(r-4.6-any)
highDmean_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
highDmean/json (API)
NEWS

# Install 'highDmean' in R:
install.packages('highDmean', repos = c('https://huaiyuzhang.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 1 scripts 209 downloads 6 exports 0 dependencies

Last updated from:4c817fbddb. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK105
source / vignettesOK141
linux-release-x86_64OK91
macos-release-arm64OK147
macos-oldrel-arm64OK177
windows-develOK59
windows-releaseOK66
windows-oldrelOK69
wasm-releaseOK84

Exports:buildDatargammashiftSKK_simSKK_testzwl_simzwl_test

Dependencies: