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Map past data to states of state-space and nonlinear ARX models

`X = data2state(sys,PastData)`

```
[X,XCov]
= data2state(sys,PastData)
```

maps
the past data to the states of a state-space or a nonlinear ARX model `X`

= data2state(`sys`

,`PastData`

)`sys`

. `X`

contains
the state values at the time instant immediately after the most recent
data sample in `PastData`

. The software computes
the state estimates by minimizing the 1-step ahead prediction error
between predicted response and output signal in `PastData`

.

`data2state`

is useful for continued model
simulation. That is, suppose you have simulated a model up to a certain
time instant and would like to then simulate the model for future
inputs. Use `data2state`

to estimate states of
the model at the beginning of the second simulation.

`findstates`

| `getDelayInfo`

| `idnlarx/findop`

| `order`

| `sim`