forecast.stl: Forecasting using stl objects

In ttnsdcn/forecast-package: Forecasting functions for time series

Description

Returns forecasts obtained by either ETS or ARIMA models applied to the seasonally adjusted data from an STL decomposition.

Usage

## S3 method for class 'stl'
forecast(object, method=c("ets","arima"), etsmodel="ZZN",
    h=frequency(object$time.series)*2, level=c(80,95), fan=FALSE, lambda=NULL, ...)
stlf(x, h=frequency(x)*2, s.window=7, method=c("ets","arima"), etsmodel="ZZN",
    level=c(80,95), fan=FALSE, lambda=NULL, ...)

Arguments

object	An object of class "stl". Usually the result of a call to stl.
x	A univariate numeric time series of class "ts"
method	Method to use for forecasting the seasonally adjusted series.
etsmodel	The ets model specification passed to ets. By default it allows any non-seasonal model. If method=="arima", this argument is ignored.
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, data transformed before model is estimated and back-transformed after forecasts are computed.
s.window	Either the character string "periodic" (default) or the span (in lags) of the loess window for seasonal extraction.
...	Other arguments passed to ets() or auto.arima().

Details

forecast.stl seasonally adjusts the data from an STL decomposition, then uses either ETS or ARIMA models to forecast the result. The seasonal component from the last year of data is added back in to the forecasts. Note that the prediction intervals ignore the uncertainty associated with the seasonal component.

stlf takes a ts argument and applies a stl decomposition before calling forecast.stl.

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.stl.

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 (possibly tranformed) x minus fitted values.
fitted	Fitted values (one-step forecasts) on transformed scale if lambda is not NULL.

Author(s)

Rob J Hyndman

See Also

forecast.ets, forecast.Arima.

Examples

fit <- stl(USAccDeaths,s.window="periodic")
plot(forecast(fit))

plot(stlf(AirPassengers, lambda=BoxCox.lambda(AirPassengers)))

ttnsdcn/forecast-package documentation built on June 1, 2019, 2:49 a.m.