Name
CL_cov2cor — Covariance to correlation matrix
Calling Sequence
[cor,sd] = CL_cov2cor(cov)
Description
-
Computes the correlation matrix cor and the standard deviations vector sd
from the covariance matrix cov.
Diagonal of covariance matrix contains variances : cov(i,i) = var(i) = sd(i)^2
Covariance and correlation matrix are linked by : cor(i,j) = cov(i,j) / (sd(i)*sd(j)) thus diagonal of correlation is cor(i,i) = 1
Correlation matrix is dimensionless
- Last update : 14/10/2009
Parameters
- cov:
covariance (hyper)matrix (p x p x N)
- cor:
correlation (hyper)matrix (p x p x N)
- sd:
standard deviations vectors (p x N)
Examples
// Random covariance matrix :
p=6; N=2;
cov = matrix(rand(1,p*p*N,"gaussian"),p,p,N);
cov = cov'*cov; // symmetric
[cor,sd] = CL_cov2cor(cov);
// Going back to the correlation :
cov2 = CL_cor2cov(cor,sd) ;