Documentation

# cov2corr

Convert covariance to standard deviation and correlation coefficient

## Syntax

``[ExpSigma,ExpCorrC] = cov2corr(ExpCovariance)``

## Description

example

````[ExpSigma,ExpCorrC] = cov2corr(ExpCovariance)` converts covariance to standard deviations and correlation coefficients.```

## Examples

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This example shows how to convert a covariance matrix to standard deviations and correlation coefficients.

```ExpCovariance = [0.25 -0.5 -0.5 4.0]; [ExpSigma, ExpCorrC] = cov2corr(ExpCovariance)```
```ExpSigma = 1×2 0.5000 2.0000 ```
```ExpCorrC = 2×2 1.0000 -0.5000 -0.5000 1.0000 ```

## Input Arguments

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Covariance matrix, specified as an `n`-by-`n` covariance matrix, where `n` is the number of random processes. For an example, see `cov` or `ewstats`.

Data Types: `double`

## Output Arguments

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Standard deviation of each process, returned as an `1`-by-`n` vector.

The entries of `ExpCorrC` range from `1` (completely correlated) to `-1` (completely anti-correlated). A value of `0` in the (i,j) entry indicates that the i'th and j'th processes are uncorrelated.

```ExpSigma(i) = sqrt( ExpCovariance(i,i) ); ExpCorrC(i,j) = ExpCovariance(i,j)/( ExpSigma(i)*ExpSigma(j) );```

Data Types: `double`

Correlation coefficients, returned as an `n`-by-`n` matrix.