ldstatsHD (version 1.0.1)

cor2mean: Average square correlation by rows

Description

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

Usage

cor2mean(mat)

Arguments

mat

\(p \times n\) matrix with the p-variate dataset.

Value

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

Details

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

References

To come

See Also

cor2mean.adj for adjusted average square correlation magnitude.

Examples

# NOT RUN {
EX1      <- pcorSimulator(nobs = 50, nclusters= 3, nnodesxcluster = c(100,30,50), 
                          pattern = "powerLaw", plus = 0)
corsEX1  <- cor2mean(t(EX1$y))

# }