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# init

Set or randomize initial parameter values

## Syntax

```m = init(m0) m = init(m0,R,pars,sp) ```

## Description

`m = init(m0)` randomizes initial parameter estimates for model structures `m0` for any linear or nonlinear identified model. It does not support `idnlgrey` models. `m` is the same model structure as `m0`, but with a different nominal parameter vector. This vector is used as the initial estimate by `pem`.

`m = init(m0,R,pars,sp)` randomizes parameters around `pars` with variances given by the row vector `R`. Parameter number k is randomized as `pars(k)` + `e*sqrt(R(k))`, where `e` is a normal random variable with zero mean and a variance of 1. The default value of `R` is all ones, and the default value of `pars` is the nominal parameter vector in `m0`.

Only models that give stable predictors are accepted. If ```sp = 'b'```, only models that are both stable and have stable predictors are accepted.

`sp = 's'` requires stability only of the model, and `sp = 'p'` requires stability only of the predictor. ```sp = 'p'``` is the default.

Sufficiently free parameterizations can be stabilized by direct means without any random search. To just stabilize such an initial model, set `R = 0`. With `R > 0`, randomization is also done.

For model structures where a random search is necessary to find a stable model/predictor, a maximum of 100 trials is made by `init`. It can be difficult to find a stable predictor for high-order systems by trial and error.

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