# setcov

Set parameter covariance data in identified model

## Syntax

``newSys = setcov(sys,cov)``

## Description

example

````newSys = setcov(sys,cov)` sets the parameter covariance of identified model `sys` as `cov`.The model parameter covariance is calculated and stored automatically when a model is estimated. Therefore, you do not need to set the parameter covariance explicitly for estimated models. Use this function for analysis, such as to study how the parameter covariance affects the response of a model obtained by explicit construction.```

## Examples

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Create a transfer function model for the following system:

`$sys0=\frac{4}{{s}^{2}+2s+1}$`

```sys0 = idtf(4,[1 2 1]); np = nparams(sys0);```

`sys0` contains `np` model parameters.

Specify the covariance values for the denominator parameters only.

```cov = zeros(np); den_index = 2:3; cov(den_index,den_index) = diag([0.04 0.001]);```

`cov` is a covariance matrix with nonzero entries for the denominator parameters.

Set the covariance for `sys0`.

`sys = setcov(sys0,cov);`

## Input Arguments

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Identified model, specified as one of the following model objects.

Parameter covariance matrix, specified as one of the following:

• Np-by-Np semi-positive definite symmetric matrix, where Np is equal to the number of parameters of `sys`.

• Structure with the following fields that describe the parameter covariance in a factored form.

• `R` — Usually the Cholesky factor of inverse of covariance

• `T` — Transformation matrix

• `Free` — Logical vector of length Np indicating if a parameter is free.

To derive the covariance matrix use the command ```cov(Free,Free) = T*inv(R'*R)*T'```.

## Output Arguments

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Identified model, returned as the same type of identified model object as `sys`. The parameter covariance matrix in `newSys` matches the new covariance matrix specified in `params`.

## Version History

Introduced in R2012a