R: Forecasting using ETS models

forecast.ets {forecast}

R Documentation

Forecasting using ETS models

Description

Returns forecasts and other information for univariate ETS models.

Usage

## S3 method for class 'ets'
forecast(object, h=ifelse(object$m>1, 2*object$m, 10), 
    level=c(80,95), fan=FALSE, simulate=FALSE, bootstrap=FALSE, 
    npaths=5000, PI=TRUE, lambda=object$lambda, ...)

Arguments

`object`	An object of class "`ets`". Usually the result of a call to `ets`.
`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.
`simulate`	If TRUE, prediction intervals produced by simulation rather than using analytic formulae.
`bootstrap`	If TRUE, and if `simulate=TRUE`, then simulation uses resampled errors rather than normally distributed errors.
`npaths`	Number of sample paths used in computing simulated prediction intervals.
`PI`	If TRUE, prediction intervals are produced, otherwise only point forecasts are calculated. If `PI` is FALSE, then `level`, `fan`, `simulate`, `bootstrap` and `npaths` are all ignored.
`lambda`	Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.
`...`	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.ets.

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)

Author(s)

Rob J Hyndman

Examples

fit <- ets(USAccDeaths)
plot(forecast(fit,h=48))

[Package forecast version 3.24 Index]