# forecast.bats

From forecast v3.18
by Rob Hyndman

##### Forecasting using BATS and TBATS models

Forecasts `h`

steps ahead with a BATS model. Prediction intervals are also produced.

- Keywords
- ts

##### Usage

```
## S3 method for class 'bats':
forecast(object, h=10, level=c(80,95), fan=FALSE, ...)
## S3 method for class 'tbats':
forecast(object, h=10, level=c(80,95), fan=FALSE, ...)
```

##### Arguments

- object
- An object of class "
`bats`

". Usually the result of a call to`bats`

. - h
- Number of periods for forecasting
- level
- Confidence level for prediction intervals.
- fan
- If TRUE, level is set to
`seq(50,99,by=1)`

. This is suitable for fan plots. - ...
- Other arguments, currently ignored.

##### Value

- An object of class "
`forecast`

".The function

`summary`

is used to obtain and print a summary of the results, while the function`plot`

produces a plot of the forecasts and prediction intervals.The generic accessor functions

`fitted.values`

and`residuals`

extract useful features of the value returned by`forecast.bats`

.An object of class

`"forecast"`

is a list containing at least the following elements: model A copy of the `bats`

objectmethod The name of the forecasting method as a character string mean Point forecasts as a time series lower Lower limits for prediction intervals upper Upper limits for prediction intervals level The confidence values associated with the prediction intervals x The original time series (either `object`

itself or the time series used to create the model stored as`object`

).residuals Residuals from the fitted model. That is x minus fitted values. fitted Fitted values (one-step forecasts)

##### References

De Livera, A.M., Hyndman, R.J., & Snyder, R. D. (2012), Forecasting time series with complex seasonal patterns using exponential smoothing, *Journal of the American Statistical Association*, to appear.

##### See Also

##### Examples

```
fit <- bats(USAccDeaths)
plot(forecast(fit))
taylor.fit <- bats(taylor)
plot(forecast(taylor.fit))
```

*Documentation reproduced from package forecast, version 3.18, License: GPL (>= 2)*

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