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HDNRA: High-Dimensional Location Testing with Normal-Reference Approaches

We provide a collection of various classical tests and latest normal-reference tests for comparing high-dimensional mean vectors including two-sample and general linear hypothesis testing (GLHT) problem. Some existing tests for two-sample problem [see Bai, Zhidong, and Hewa Saranadasa.(1996) <https://www.jstor.org/stable/24306018>; Chen, Song Xi, and Ying-Li Qin.(2010) <doi:10.1214/09-aos716>; Srivastava, Muni S., and Meng Du.(2008) <doi:10.1016/j.jmva.2006.11.002>; Srivastava, Muni S., Shota Katayama, and Yutaka Kano.(2013)<doi:10.1016/j.jmva.2012.08.014>]. Normal-reference tests for two-sample problem [see Zhang, Jin-Ting, Jia Guo, Bu Zhou, and Ming-Yen Cheng.(2020) <doi:10.1080/01621459.2019.1604366>; Zhang, Jin-Ting, Bu Zhou, Jia Guo, and Tianming Zhu.(2021) <doi:10.1016/j.jspi.2020.11.008>; Zhang, Liang, Tianming Zhu, and Jin-Ting Zhang.(2020) <doi:10.1016/j.ecosta.2019.12.002>; Zhang, Liang, Tianming Zhu, and Jin-Ting Zhang.(2023) <doi:10.1080/02664763.2020.1834516>; Zhang, Jin-Ting, and Tianming Zhu.(2022) <doi:10.1080/10485252.2021.2015768>; Zhang, Jin-Ting, and Tianming Zhu.(2022) <doi:10.1007/s42519-021-00232-w>; Zhu, Tianming, Pengfei Wang, and Jin-Ting Zhang.(2023) <doi:10.1007/s00180-023-01433-6>]. Some existing tests for GLHT problem [see Fujikoshi, Yasunori, Tetsuto Himeno, and Hirofumi Wakaki.(2004) <doi:10.14490/jjss.34.19>; Srivastava, Muni S., and Yasunori Fujikoshi.(2006) <doi:10.1016/j.jmva.2005.08.010>; Yamada, Takayuki, and Muni S. Srivastava.(2012) <doi:10.1080/03610926.2011.581786>; Schott, James R.(2007) <doi:10.1016/j.jmva.2006.11.007>; Zhou, Bu, Jia Guo, and Jin-Ting Zhang.(2017) <doi:10.1016/j.jspi.2017.03.005>]. Normal-reference tests for GLHT problem [see Zhang, Jin-Ting, Jia Guo, and Bu Zhou.(2017) <doi:10.1016/j.jmva.2017.01.002>; Zhang, Jin-Ting, Bu Zhou, and Jia Guo.(2022) <doi:10.1016/j.jmva.2021.104816>; Zhu, Tianming, Liang Zhang, and Jin-Ting Zhang.(2022) <doi:10.5705/ss.202020.0362>; Zhu, Tianming, and Jin-Ting Zhang.(2022) <doi:10.1007/s00180-021-01110-6>; Zhang, Jin-Ting, and Tianming Zhu.(2022) <doi:10.1016/j.csda.2021.107385>].

Version: 2.0.1
Depends: R (≥ 4.0)
Imports: expm, Rcpp, Rdpack, readr, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: devtools, dplyr, knitr, rmarkdown, spelling, testthat (≥ 3.0.0), tidyr
Published: 2024-10-22
DOI: 10.32614/CRAN.package.HDNRA
Author: Pengfei Wang [aut, cre], Shuqi Luo [aut], Tianming Zhu [aut], Bu Zhou [aut]
Maintainer: Pengfei Wang <nie23.wp8738 at e.ntu.edu.sg>
BugReports: https://github.com/nie23wp8738/HDNRA/issues
License: GPL (≥ 3)
URL: https://nie23wp8738.github.io/HDNRA/
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: HDNRA results

Documentation:

Reference manual: HDNRA.pdf

Downloads:

Package source: HDNRA_2.0.1.tar.gz
Windows binaries: r-devel: HDNRA_2.0.1.zip, r-release: HDNRA_2.0.1.zip, r-oldrel: HDNRA_2.0.1.zip
macOS binaries: r-release (arm64): HDNRA_2.0.1.tgz, r-oldrel (arm64): HDNRA_2.0.1.tgz, r-release (x86_64): HDNRA_2.0.1.tgz, r-oldrel (x86_64): HDNRA_2.0.1.tgz
Old sources: HDNRA archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=HDNRA to link to this page.

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.