HS_empirical_bootstrap_test {covsep} | R Documentation |
Empirical bootstrap test for separability of covariance structure using Hilbert–Schmidt distance
Description
Empirical bootstrap test for separability of covariance structure using Hilbert–Schmidt distance
Usage
HS_empirical_bootstrap_test(Data, B = 100, verbose = TRUE)
Arguments
Data |
a (non-empty) |
B |
number of bootstrap replicates to be used. |
verbose |
logical parameter for printing progress |
Value
The p-value of the test.
Details
This function performs the test of separability of the covariance structure for a random surface (introduced in the paper http://arxiv.org/abs/1505.02023), when generated from a Gaussian process. The sample surfaces need to be measured on a common regular grid. The test considers the Hilbert–Schmidt distance between the sample covariance and its separable approximation. WE DO NOT RECOMMEND THIS TEST, as it is does not have the correct level, nor good power.
Examples
data(SurfacesData)
HS_empirical_bootstrap_test(SurfacesData)
HS_empirical_bootstrap_test(SurfacesData, B = 100)