cor2mean: Average square correlation by rows In ldstatsHD: Linear Dependence Statistics for High-Dimensional Data

Description

Finds in a computationally fast algorithm the average square correlation magnitude for every variable of a dataset.

Usage

 1 cor2mean(mat) 

Arguments

 mat p \times n matrix with the p-variate dataset.

Details

It is especially suitable for high dimensions. For instance it handles well dimensions of order of thousands.

Value

The average square correlation magnitude of the sample correlation matrix (including the diagonal) for every variable in mat.

Author(s)

Mayer, Claus, Adria Caballe and Natalia Bochkina.

References

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))