corr2cov

Convert standard deviation and correlation to covariance

Syntax

ExpCovariance = corr2cov(ExpSigma)
ExpCovariance = corr2cov(___,ExpCorrC)

Description

example

ExpCovariance = corr2cov(ExpSigma) converts standard deviation and correlation to covariance.

example

ExpCovariance = corr2cov(___,ExpCorrC) specifies options using one or more optional arguments in addition to the input arguments in the previous syntax.

Examples

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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

Input Arguments

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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.

Data Types: double

(Optional) Correlation matrix, specified as an n-by-n correlation coefficient matrix. If ExpCorrC is not specified, the processes are assumed to be uncorrelated, and the identity matrix is used.

Data Types: double

Output Arguments

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Covariance matrix, returned as an n-by-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) 

Introduced before R2006a