# forecast.bats

From forecast v7.2
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

```
"forecast"(object, h, level=c(80,95), fan=FALSE, biasadj=FALSE, ...)
"forecast"(object, h, level=c(80,95), fan=FALSE, biasadj=FALSE, ...)
```

##### Arguments

- object
- An object of class "
`bats`

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

. - h
- Number of periods for forecasting. Default value is twice the largest seasonal period (for seasonal data) or ten (for non-seasonal data).
- level
- Confidence level for prediction intervals.
- fan
- If TRUE, level is set to
`seq(51,99,by=3)`

. This is suitable for fan plots. - biasadj
- Use adjusted back-transformed mean for Box-Cox transformations. If TRUE, point forecasts and fitted values are mean forecast. Otherwise, these points can be considered the median of the forecast densities.
- ...
- Other arguments, currently ignored.

##### Value

`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:
is a list containing at least the following elements:##### References

De Livera, A.M., Hyndman, R.J., & Snyder, R. D. (2011), Forecasting time series with complex seasonal patterns using exponential smoothing, *Journal of the American Statistical Association*, **106**(496), 1513-1527.

##### See Also

##### Examples

```
## Not run:
# fit <- bats(USAccDeaths)
# plot(forecast(fit))
#
# taylor.fit <- bats(taylor)
# plot(forecast(taylor.fit))
# ## End(Not run)
```

*Documentation reproduced from package forecast, version 7.2, License: GPL (>= 2)*

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