Finds in a computationally fast algorithm the average square correlation magnitude for every variable of a dataset.
1  cor2mean(mat)

mat 
p \times n matrix with the pvariate dataset. 
It is especially suitable for high dimensions. For instance it handles well dimensions of order of thousands.
The average square correlation magnitude of the sample correlation matrix (including the diagonal) for every variable in mat
.
Mayer, Claus, Adria Caballe and Natalia Bochkina.
To come
cor2mean.adj
for adjusted average square correlation magnitude.
1 2 3  EX1 < pcorSimulator(nobs = 50, nclusters= 3, nnodesxcluster = c(100,30,50),
pattern = "powerLaw", plus = 0)
corsEX1 < cor2mean(t(EX1$y))

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