# Forecasting using BATS and TBATS models

Source:`R/forecastBATS.R`

, `R/forecastTBATS.R`

`forecast.bats.Rd`

Forecasts `h`

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

## 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

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`

object- method
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.

- fitted
Fitted values (one-step forecasts)

## 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.