Description Usage Arguments Value References See Also
The two-sample covariance test using random projections proposed in Wu and Li (2015) "Tests for High-Dimensional Covariance Matrices Using Random Matrix Projection".
1 | WL.randProj.test(X, Y, nproj = 100, useMC = FALSE, mc.cores = 1)
|
X |
n1 by p matrix, observation of the first population, columns are features |
Y |
n2 by p matrix, observation of the second population, columns are features |
nproj |
number of random projections to use |
useMC |
logical variable indicating whether to use multicore parallelization.
R packages |
mc.cores |
decide the number of cores to use when |
A list containing the following components:
test.stat |
test statistic |
pVal |
the p-value calculated using the limiting distribution (max of independent standard normal) |
Wu and Li (2015) "Tests for High-Dimensional Covariance Matrices Using Random Matrix Projection", arXiv preprint arXiv:1511.01611.
Cai.max.test()
, Chang.maxBoot.test()
, LC.U.test()
,
Schott.Frob.test()
.
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