forecast.HoltWinters: Forecasting using Holt-Winters objects
In ttnsdcn/forecast-package: Forecasting functions for time series

Description Usage Arguments Details Value Author(s) See Also Examples

Returns forecasts and other information for univariate Holt-Winters time series models.

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## S3 method for class 'HoltWinters'
forecast(object, h=ifelse(frequency(object$x)>1,2*frequency(object$x),10),
    level=c(80,95),fan=FALSE,lambda=NULL,...)

`object`	An object of class "`HoltWinters`". Usually the result of a call to `HoltWinters`.
`h`	Number of periods for forecasting
`level`	Confidence level for prediction intervals.
`fan`	If TRUE, level is set to seq(50,99,by=1). This is suitable for fan plots.
`lambda`	Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.
`...`	Other arguments.

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.

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 as `object`).
`residuals`	Residuals from the fitted model. That is x minus fitted values.
`fitted`	Fitted values (one-step forecasts)