highDmean: Testing Two-Sample Mean in High Dimension
Implements the high-dimensional two-sample test
proposed by Zhang (2019) <http://hdl.handle.net/2097/40235>.
It also implements the test proposed by Srivastava, Katayama,
and Kano (2013) <doi:10.1016/j.jmva.2012.08.014>. These tests
are particularly suitable to high dimensional data from two populations
for which the classical multivariate Hotelling's T-square test fails due
to sample sizes smaller than dimensionality. In this case, the ZWL and ZWLm
tests proposed by Zhang (2019) <http://hdl.handle.net/2097/40235>,
referred to as zwl_test() in this package, provide a reliable and powerful test.
Version: |
0.1.0 |
Depends: |
R (≥ 3.1.0) |
Imports: |
stats |
Published: |
2020-06-12 |
Author: |
Huaiyu Zhang, Haiyan Wang |
Maintainer: |
Huaiyu Zhang <huaiyuzhang1988 at gmail.com> |
License: |
GPL-2 |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
highDmean results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=highDmean
to link to this page.