highd2means-package {highd2means}R Documentation

High-Dimensional Tests for two Population Mean Vectors

Description

The package contains a few tests for the case of two high-dimensional population mean vectors. The user has the option to compute the asymptotic, the permutation or the bootstrap based p-value of the test.The tests are based on three other packages, namely the highmean, highDmean and the PEtests. We took the codes, modified them and made them more efficient.

Details

Package: highd2means
Type: Package
Version: 1.0
Date: 2024-08-17
License: GPL-2

Maintainers

Michail Tsagris mtsagris@uoc.gr.

Author(s)

Michail Tsagris mtsagris@uoc.gr and Manos Papadakis papadakm95@gmail.com.

References

Bai Z.D. and Saranadasa H. (1996). Effect of high dimension: by an example of a two sample problem. Statistica Sinica, 6(2): 311–329.

Cai T.T., Liu W., and Xia Y. (2014). Two-sample test of high dimensional means under dependence. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 76(2): 349–372.

Chen S.X. and Qin Y.L. (2010). A two-sample test for high-dimensional data with applications to gene-set testing. The Annals of Statistics, 38(2) 808–835.

Chen S.X., Li J., and Zhong P.S. (2014). Two-Sample Tests for High Dimensional Means with Thresholding and Data Transformation. arXiv preprint arXiv:1410.2848.

Srivastava M.S. and Du M. (2008). A test for the mean vector with fewer observations than the dimension. Journal of Multivariate Analysis, 99(3): 386–402.

Srivastava, M.S., Katayama, S., and Kano, Y. (2013). A two sample test in high dimensional data. Journal of Multivariate Analysis, 114: 349–358.

Yu X., Li D., Xue L. and Li, R. (2023). Power-enhanced simultaneous test of high-dimensional mean vectors and covariance matrices with application to gene-set testing. Journal of the American Statistical Association, 118(544): 2548–2561.


[Package highd2means version 1.0 Index]