# Documentation

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# corr2cov

Convert standard deviation and correlation to covariance

## Syntax

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

## Arguments

 `ExpSigma` Vector of length n with the standard deviations of each process. n is the number of random processes. `ExpCorrC` (Optional) n-by-n correlation coefficient matrix. If `ExpCorrC` is not specified, the processes are assumed to be uncorrelated, and the identity matrix is used.

## Description

`corr2cov` converts standard deviation and correlation to covariance.

`ExpCovariance` is an n-by-n covariance matrix, where n is the number of processes.

```ExpCov(i,j) = ExpCorrC(i,j)*ExpSigma(i)*ExpSigma(j) ```

## Examples

collapse all

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 = 0.2500 -0.5000 -0.5000 4.0000 ```

## See Also

#### Introduced before R2006a

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