# arima.errors

From forecast v2.19
by Rob Hyndman

##### ARIMA errors

Returns original time series after adjusting for
regression variables. These are not the same as the residuals.
If there are no regression variables in the ARIMA model, then
the errors will be identical to the original series. If there
are regression variables in the ARIMA model, then the errors
will be equal to the original series minus the effect of the
regression variables, but leaving in the serial correlation
that is modelled with the AR and MA terms. If you want the
"residuals", then use `residuals(z).`

.

- Keywords
- ts

##### Usage

`arima.errors(z)`

##### Arguments

- z
- Fitted ARIMA model from
`arima`

##### Value

- A time series containing the "errors".

##### See Also

##### Examples

```
ukdeaths.fit <- Arima(UKDriverDeaths,c(1,0,1),c(0,1,1),xreg=Seatbelts[,"law"])
ukdeaths.errors <- arima.errors(ukdeaths.fit)
par(mfrow=c(2,1))
plot(UKDriverDeaths)
plot(ukdeaths.errors)
```

*Documentation reproduced from package forecast, version 2.19, License: GPL (>= 2)*

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