Convert standard deviation and correlation to covariance
ExpCovariance = corr2cov(ExpSigma)
ExpCovariance = corr2cov(___,ExpCorrC)
This example shows how to convert standard deviation and correlation to covariance.
ExpSigma = [0.5 2.0]; ExpCorrC = [1.0 -0.5 -0.5 1.0]; ExpCovariance = corr2cov(ExpSigma, ExpCorrC)
ExpCovariance = 2×2 0.2500 -0.5000 -0.5000 4.0000
ExpSigma— Standard deviations of each process
Standard deviations of each process, specified as a vector of length
n with the standard deviations of each process.
n is the number of random processes.
ExpCorrC— Correlation matrix
(Optional) Correlation matrix, specified as an
n correlation coefficient
ExpCorrC is not specified, the processes are
assumed to be uncorrelated, and the identity matrix is used.
ExpCovariance— Covariance matrix
Covariance matrix, returned as an
n covariance matrix, where
n is the number of processes.
The (i,j) entry is the expectation of the i'th fluctuation from the mean times the j'th fluctuation from the mean.
ExpCov(i,j) = ExpCorrC(i,j)*ExpSigma(i)*ExpSigma(j)