Estimates the mmode covariance matrix from an array of arrayvalued observations.
1  mModeCovariance(x, m, center = TRUE)

x 
Array of order higher than two with the last dimension corresponding to the sampling units. 
m 
The mode with respect to which the covariance matrix is to be computed. 
center 
Logical, indicating whether the observations should be centered prior to computing the covariance matrix. Default is 
The mmode covariance matrix provides a higher order analogy for the ordinary covariance matrix of a random vector and is computed for a random tensor X of size p_1 x p_2 x ... x p_r as Cov_m(X) = E(X(m) X(m)^T)/(p_1 ... p_(m1) p_(m+1) ... p_r), where X(m) is the centered mflattening of X. The algorithm computes the estimate of this based on the sample x
.
The m
mode covariance matrix of x
having the size p_m x p_m.
Joni Virta
Virta, J., Li, B., Nordhausen, K. and Oja, H., (2016), Independent component analysis for tensorvalued data, submitted, ???, ???–???. Preprint available on ArXiv http://arxiv.org/abs/1602.00879.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs with the GitHub issue tracker.
All documentation is copyright its authors; we didn't write any of that.