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Provides inverse-free high-dimensional location tests for two-sample and general linear hypothesis testing (GLHT) problems under equal or unequal covariance structures. The package implements classical normal-approximation procedures, scale-invariant procedures, normal-reference procedures based on covariance-matched Gaussian companions, and F-type normal-reference calibrations for heteroscedastic Behrens-Fisher and GLHT settings. Implemented two-sample normal-approximation and scale-invariant procedures include Bai and Saranadasa (1996) <https://www.jstor.org/stable/24306018>, Chen and Qin (2010) <doi:10.1214/09-aos716>, Srivastava and Du (2008) <doi:10.1016/j.jmva.2006.11.002>, and Srivastava et al. (2013) <doi:10.1016/j.jmva.2012.08.014>. Implemented two-sample normal-reference procedures include Zhang, Guo, Zhou and Cheng (2020) <doi:10.1080/01621459.2019.1604366>, Zhang, Zhou, Guo and Zhu (2021) <doi:10.1016/j.jspi.2020.11.008>, Zhang, Zhu and Zhang (2020) <doi:10.1016/j.ecosta.2019.12.002>, Zhang, Zhu and Zhang (2023) <doi:10.1080/02664763.2020.1834516>, Zhang and Zhu (2022) <doi:10.1080/10485252.2021.2015768>, Zhang and Zhu (2022) <doi:10.1007/s42519-021-00232-w>, and Zhu, Wang and Zhang (2023) <doi:10.1007/s00180-023-01433-6>. Implemented GLHT normal-approximation procedures include Fujikoshi et al. (2004) <doi:10.14490/jjss.34.19>, Srivastava and Fujikoshi (2006) <doi:10.1016/j.jmva.2005.08.010>, Yamada and Srivastava (2012) <doi:10.1080/03610926.2011.581786>, Schott (2007) <doi:10.1016/j.jmva.2006.11.007>, and Zhou, Guo and Zhang (2017) <doi:10.1016/j.jspi.2017.03.005>. Implemented GLHT normal-reference procedures include Zhang, Guo and Zhou (2017) <doi:10.1016/j.jmva.2017.01.002>, Zhang, Zhou and Guo (2022) <doi:10.1016/j.jmva.2021.104816>, Zhu, Zhang and Zhang (2022) <doi:10.5705/ss.202020.0362>, Zhu and Zhang (2022) <doi:10.1007/s00180-021-01110-6>, Zhang and Zhu (2022) <doi:10.1016/j.csda.2021.107385>, and Cao et al. (2024) <doi:10.1007/s00362-024-01530-8>. The package also includes the random-integration normal-approximation GLHT procedure of Li et al. (2025) <doi:10.1007/s00362-024-01624-3>. A package-level overview is given in Wang, Zhu and Zhang (2026) <doi:10.1016/j.csda.2025.108269>.
| Version: | 2.1.0 |
| Depends: | R (≥ 4.0.0) |
| Imports: | expm, Rcpp, Rdpack, readr, stats, utils |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | devtools, dplyr, knitr, rmarkdown, spelling, testthat (≥ 3.0.0), tidyr |
| Published: | 2026-04-29 |
| 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://github.com/nie23wp8738/HDNRA, https://nie23wp8738.github.io/HDNRA/ |
| NeedsCompilation: | yes |
| SystemRequirements: | OpenMP |
| Language: | en-US |
| Materials: | README, NEWS |
| CRAN checks: | HDNRA results |
| Reference manual: | HDNRA.html , HDNRA.pdf |
| Package source: | HDNRA_2.1.0.tar.gz |
| Windows binaries: | r-devel: HDNRA_2.1.0.zip, r-release: HDNRA_2.1.0.zip, r-oldrel: HDNRA_2.1.0.zip |
| macOS binaries: | r-release (arm64): HDNRA_2.1.0.tgz, r-oldrel (arm64): HDNRA_2.1.0.tgz, r-release (x86_64): HDNRA_2.1.0.tgz, r-oldrel (x86_64): HDNRA_2.1.0.tgz |
| Old sources: | HDNRA archive |
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