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