Description Usage Arguments Value References See Also
Testing the equality of two high-dimensional covariance matrices based on the L_\infinity norm, proposed in Cai, Liu and Xia (2013) "Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings".
1 | Cai.max.test(X, Y)
|
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 |
A list with the following components:
Mn |
the largest M_ij as defined in Cai (2013) equation (2) |
test.stat |
test statistic (calculated as Mn - 4*log p + log log p) |
pVal |
p-value given by the limiting distribution (Gumbol distribution) |
Cai, Liu and Xia (2013) "Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings", Journal of the American Statistical Association.
Chang.maxBoot.test()
, LC.U.test()
, WL.randProj.test()
,
Schott.Frob.test()
.
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