Name

CL_cor2cov — Correlation to covariance matrix

Calling Sequence

   cov = CL_cor2cov(cor,sd)
   
   

Description

  • Computes the the covariance matrix cov from the correlation matrix cor and the standard deviations vector sd

    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

cor:

correlation (hyper)matrix (p x p x N)

sd:

standard deviations vectors (p x N)

cov:

covariance (hyper)matrix (p x p x N)

Authors

CNES - DCT/SB

See also

CL_cov2cor

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) ;