Description Usage Arguments Value See Also
Perform the wild boostrap procedure for testing two-sample covariance matrices in Chang et al. (2016).
1 2 | Chang.wildBootstrap(X, Y, sigma.x, sigma.y, Tdenominator, nresample = 1000,
useMC = TRUE, 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 |
sigma.x |
p-by-p matrix, sample covariance of X, pre-calculated |
sigma.y |
p-by-p matrix, sample covariance of X, pre-calculated |
Tdenominator |
the denominator of the test statistics, which is pre-calculated and remains unchanged in bootstrap. |
nresample |
the number of bootstraps to perform |
useMC |
logical variable indicating whether to use multicore parallelization.
R packages |
mc.cores |
decide the number of cores to use when |
A numeric vector with length nresample
, containing the test statistics
in wild boostrap repetitions.
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