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>].

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Queries data from WHOIS servers.

This package selects genes associated with survival.

This package provides Pure Rust MessagePack serialization implementation.

RubyRC4 is a pure Ruby implementation of the RC4 algorithm.

Fits linear models to repeated ordinal scores using GEE methodology.

Interface to the yacas computer algebra system (<http://www.yacas.org/>).

The goal of ralger is to facilitate web scraping in R.

R access to the FOAAS (F... Off As A Service) web service is provided.

Analyzes and predicts from matrix population models (Caswell 2006) <doi:10.1002/9781118445112.stat07481>.

This package provides a web interface to compute transcriptional regulatory modules with rTRM.

rGADEM is an efficient de novo motif discovery tool for large-scale genomic sequence data.

RJB is a bridge program that connects Ruby and Java via the Java Native Interface.

This package is used for the analysis of long-range chromatin interactions from 3C-seq assay.

Parser generator for R using combinatory parsers. It is inspired by combinatory parsers developed in Haskell.

This package provides a friendly, object oriented API for creating PowerPoint slide decks in R.

Rcpp11 includes a header only C++11 library that facilitates integration between R and modern C++.

Robust pairwise correlations based on estimates of scale, particularly on "FastQn" one-step M-estimate.

Truncated Newton function minimization with bounds constraints based on the Matlab'/'Octave codes of Stephen Nash.

This package provides an iteration of the DEoptim function. It performs global optimization by differential evolution.

Recursive display of names and paths of all the items nested within sublists of a list object.

Generate random user data from the Random User Generator API. For more information, see <https://randomuser.me/>.

Functionality to download stock prices, cryptocurrency data, and more from the Tiingo API <https://api.tiingo.com/>.