Description Usage Arguments Value Author(s) Examples
Testing the equality of two sample covariance matrices in high dimension using different methods.
1 | testCov(X, Y, method = "ALL", J = 2500, alpha = 0.05, n.core = 1)
|
X |
the n x p training data, could be a |
Y |
the n x p training data matrix, could be a |
method |
a string incidating the method for the test. The current available
methods are |
J |
the number of repetition in the test |
alpha |
the significant level of the test. |
n.core |
the number of cores to be used in parallel when |
For any single method, the function returns an htest
object.
For method ALL
: A list of four htest
objects.
HD refers to "Chang, J., Zhou, W., Zhou, W.-X., and Wang, L. (2016). Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering. Biometrics. To appear"#'
CLX refers to "Cai, T. T., Liu, W., and Xia, Y. (2013). Two-sample covariance matrix testing and support recovery in high-dimensional and sparse settings. Journal of the American Statistical Association 108, 265-277."
Sc refers to "Schott, J. R. (2007). A test for the equality of covariance matrices when the dimension is large relative to the sample size. Computational Statistics and Data Analysis 51, 6535-6542."
Tong He
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