Forecasts h steps ahead with a BATS model. Prediction intervals are
also produced.
# S3 method for bats
forecast(object, h, level = c(80, 95), fan = FALSE, biasadj = NULL, ...)# S3 method for tbats
forecast(object, h, level = c(80, 95), fan = FALSE, biasadj = NULL, ...)
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:
A copy of the bats object
The name of the forecasting method as a character string
Point forecasts as a time series
Lower limits for prediction intervals
Upper limits for prediction intervals
The confidence values associated with the prediction intervals
The original time series (either object itself or the time
series used to create the model stored as object).
Residuals from the fitted model.
Fitted values (one-step forecasts)
An object of class "bats". Usually the result of a call
to bats.
Number of periods for forecasting. Default value is twice the largest seasonal period (for seasonal data) or ten (for non-seasonal data).
Confidence level for prediction intervals.
If TRUE, level is set to seq(51,99,by=3). This is suitable
for fan plots.
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.
Slava Razbash and Rob J Hyndman
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.
bats, tbats,forecast.ets.
if (FALSE) {
fit <- bats(USAccDeaths)
plot(forecast(fit))
taylor.fit <- bats(taylor)
plot(forecast(taylor.fit))
}
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