Zip containing the full data set for each matrix at each time point, the randomised data sets (separated by modularity and nestedness) and the r code used to analyse data.
This work introduces the Matrix Minimum Covariance Determinant (MMCD) method, a novel robust location and covariance estimation procedure designed for data that are naturally represented in the form o
The S-Divergence is a distance like function on the convex cone of positive definite matrices, which is motivated from convex optimization. In this paper, we will prove some inequalities for Kubo-Ando
Confidence intervals and mean of the complete set of posterior distribuition of 1000 variance and covariance G-matrices for control t line in .csv format.