Returns forecasts and other information for bagged models.
# S3 method for baggedModel
forecast(
object,
h = ifelse(frequency(object$y) > 1, 2 * frequency(object$y), 10),
...
)An object of class "baggedModel" resulting from a call to
baggedModel.
Number of periods for forecasting.
Other arguments, passed on to the forecast function of the original method
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.
An object of class "forecast" is a list containing at least the
following elements:
A list containing information about the fitted model
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).
The external regressors used in fitting (if given).
Residuals from the fitted model. That is x minus fitted values.
Fitted values (one-step forecasts)
Intervals are calculated as min and max values over the point forecasts from the models in the ensemble. I.e., the intervals are not prediction intervals, but give an indication of how different the forecasts within the ensemble are.
Bergmeir, C., R. J. Hyndman, and J. M. Benitez (2016). Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation. International Journal of Forecasting 32, 303-312.
# NOT RUN {
fit <- baggedModel(WWWusage)
fcast <- forecast(fit)
plot(fcast)
# }
# NOT RUN {
fit2 <- baggedModel(WWWusage, fn="auto.arima")
fcast2 <- forecast(fit2)
plot(fcast2)
accuracy(fcast2)
# }
# NOT RUN {
# }
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