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: 1.0.0
Depends: R (≥ 2.10)
Imports: expm, Rcpp, Rdpack, readr, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: devtools, dplyr, knitr, rmarkdown, spelling, testthat (≥ 3.0.0), tidyr
Published: 2024-02-27
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


Reference manual: HDNRA.pdf


Package source: HDNRA_1.0.0.tar.gz
Windows binaries: r-devel: HDNRA_1.0.0.zip, r-release: HDNRA_1.0.0.zip, r-oldrel: HDNRA_1.0.0.zip
macOS binaries: r-release (arm64): HDNRA_1.0.0.tgz, r-oldrel (arm64): HDNRA_1.0.0.tgz, r-release (x86_64): HDNRA_1.0.0.tgz, r-oldrel (x86_64): HDNRA_1.0.0.tgz


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