R: Forecasting using BATS and TBATS models

forecast.bats {forecast} | R Documentation

## Forecasting using BATS and TBATS models

### Description

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

### Usage

    ## S3 method for class 'bats'
    forecast(object, h, level = c(80, 95), fan = FALSE,
      biasadj = NULL, ...)

    ## S3 method for class 'tbats'
    forecast(object, h, level = c(80, 95), fan = FALSE,
      biasadj = NULL, ...)

### 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)

### Author(s)

Slava Razbash and Rob J Hyndman

### 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

`bats`, `tbats`,`forecast.ets`.

### Examples

    ## Not run:
    fit <- bats(USAccDeaths)
    plot(forecast(fit))

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

    ## End(Not run)

[Package forecast version 8.4 Index]