Package: HDNRA 2.0.1

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>].

Authors:Pengfei Wang [aut, cre], Shuqi Luo [aut], Tianming Zhu [aut], Bu Zhou [aut]

HDNRA_2.0.1.tar.gz
HDNRA_2.0.1.zip(r-4.5)HDNRA_2.0.1.zip(r-4.4)HDNRA_2.0.1.zip(r-4.3)
HDNRA_2.0.1.tgz(r-4.4-x86_64)HDNRA_2.0.1.tgz(r-4.4-arm64)HDNRA_2.0.1.tgz(r-4.3-x86_64)HDNRA_2.0.1.tgz(r-4.3-arm64)
HDNRA_2.0.1.tar.gz(r-4.5-noble)HDNRA_2.0.1.tar.gz(r-4.4-noble)
HDNRA_2.0.1.tgz(r-4.4-emscripten)HDNRA_2.0.1.tgz(r-4.3-emscripten)
HDNRA.pdf |HDNRA.html
HDNRA/json (API)
NEWS

# Install 'HDNRA' in R:
install.packages('HDNRA', repos = c('https://nie23wp8738.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/nie23wp8738/hdnra/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

3.80 score 14 scripts 308 downloads 22 exports 32 dependencies

Last updated 1 months agofrom:03cf8d0a85. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-win-x86_64OKNov 21 2024
R-4.5-linux-x86_64OKNov 21 2024
R-4.4-win-x86_64OKNov 21 2024
R-4.4-mac-x86_64OKNov 21 2024
R-4.4-mac-aarch64OKNov 21 2024
R-4.3-win-x86_64OKNov 21 2024
R-4.3-mac-x86_64OKNov 21 2024
R-4.3-mac-aarch64OKNov 21 2024

Exports:BS1996.TS.NABTCQ2010.TSBF.NABTFHW2004.GLHT.NABTNRtest.objectS2007.ks.NABTSD2008.TS.NABTSF2006.GLHT.NABTSKK2013.TSBF.NABTYS2012.GLHT.NABTZGZ2017.GLHT.2cNRTZGZ2017.GLHTBF.NABTZGZC2020.TS.2cNRTZWZ2023.TSBF.2cNRTZZ2022.GLHT.3cNRTZZ2022.GLHTBF.3cNRTZZ2022.TS.3cNRTZZ2022.TSBF.3cNRTZZG2022.GLHTBF.2cNRTZZGZ2021.TSBF.2cNRTZZZ2020.TS.2cNRTZZZ2022.GLHT.2cNRTZZZ2023.TSBF.2cNRT

Dependencies:bitbit64clicliprcpp11crayonexpmfansigluehmslatticelifecyclemagrittrMatrixpillarpkgconfigprettyunitsprogressR6rbibutilsRcppRcppArmadilloRdpackreadrrlangtibbletidyselecttzdbutf8vctrsvroomwithr

Readme and manuals

Help Manual

Help pageTopics
Normal-approximation-based test for two-sample problem proposed by Bai and Saranadasa (1996)BS1996.TS.NABT
HDNRA_data cornealcorneal
HDNRA_data COVID19COVID19
Normal-approximation-based test for two-sample BF problem proposed by Chen and Qin (2010)CQ2010.TSBF.NABT
Normal-approximation-based test for GLHT problem proposed by Fujikoshi et al. (2004)FHW2004.GLHT.NABT
S3 Class "NRtest"NRtest.object
Print Method for S3 Class "NRtest"print.NRtest
Normal-approximation-based test for one-way MANOVA problem proposed by Schott (2007)S2007.ks.NABT
Normal-approximation-based test for two-sample problem proposed by Srivastava and Du (2008)SD2008.TS.NABT
Normal-approximation-based test for GLHT problem proposed by Srivastava and Fujikoshi (2006)SF2006.GLHT.NABT
Normal-approximation-based test for two-sample BF problem proposed by Srivastava et al. (2013)SKK2013.TSBF.NABT
Normal-approximation-based test for GLHT problem proposed by Yamada and Srivastava (2012)YS2012.GLHT.NABT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for GLHT problem proposed Zhang et al. (2017)ZGZ2017.GLHT.2cNRT
Normal-approximation-based test for GLHT problem under heteroscedasticity proposed by Zhou et al. (2017)ZGZ2017.GLHTBF.NABT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for two-sample problem proposed by Zhang et al. (2020)ZGZC2020.TS.2cNRT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for two-sample BF problem proposed by Zhu et al. (2023)ZWZ2023.TSBF.2cNRT
Normal-reference-test with three-cumulant (3-c) matched $\chi^2$-approximation for GLHT problem proposed by Zhu and Zhang (2022)ZZ2022.GLHT.3cNRT
Normal-reference-test with three-cumulant (3-c) matched $\chi^2$-approximation for GLHT problem under heteroscedasticity proposed by Zhang and Zhu (2022)ZZ2022.GLHTBF.3cNRT
Normal-reference-test with three-cumulant (3-c) matched $\chi^2$-approximation for two-sample problem proposed by Zhang and Zhu (2022)ZZ2022.TS.3cNRT
Normal-reference-test with three-cumulant (3-c) matched $\chi^2$-approximation for two-sample BF problem proposed by Zhang and Zhu (2022)ZZ2022.TSBF.3cNRT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for GLHT problem under heteroscedasticity proposed by Zhang et al. (2022)ZZG2022.GLHTBF.2cNRT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for two-sample BF problem proposed by Zhang et al. (2021)ZZGZ2021.TSBF.2cNRT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for two-sample problem proposed by Zhang et al. (2020)ZZZ2020.TS.2cNRT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for GLHT problem proposed by Zhu et al. (2022)ZZZ2022.GLHT.2cNRT
Normal-reference-test with two-cumulant (2-c) matched $\chi^2$-approximation for two-sample BF problem proposed by Zhang et al. (2023)ZZZ2023.TSBF.2cNRT