Returns forecasts and other information for univariate Holt-Winters time series models.
Arguments
- object
An object of class "
HoltWinters
". Usually the result of a call toHoltWinters
.- h
Number of periods for forecasting
- level
Confidence level for prediction intervals.
- fan
If TRUE, level is set to seq(51,99,by=3). This is suitable for fan plots.
- lambda
Box-Cox transformation parameter. If
lambda="auto"
, then a transformation is automatically selected usingBoxCox.lambda
. The transformation is ignored if NULL. Otherwise, data transformed before model is estimated.- biasadj
Use adjusted back-transformed mean for Box-Cox transformations. If transformed data is used to produce forecasts and fitted values, a regular back transformation will result in median forecasts. If biasadj is TRUE, an adjustment will be made to produce mean forecasts and fitted values.
- ...
Other arguments.
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.HoltWinters
.
An object of class "forecast"
is a list containing at least the
following elements:
- model
A list containing information about the fitted model
- 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 asobject
).- residuals
Residuals from the fitted model.
- fitted
Fitted values (one-step forecasts)
Details
This function calls predict.HoltWinters
and constructs
an object of class "forecast
" from the results.
It is included for completeness, but the ets
is recommended
for use instead of HoltWinters
.
Examples
fit <- HoltWinters(WWWusage,gamma=FALSE)
plot(forecast(fit))