Skip to Content

forecast.stl {forecast}

Forecasting using stl objects
Package: 
forecast
Version: 
5.1

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","naive","rwdrift"), 
    etsmodel="ZZN", h=frequency(object$time.series)*2, level=c(80,95), 
    fan=FALSE, lambda=NULL, xreg=NULL, newxreg=NULL, ...)
stlf(x, h=frequency(x)*2, s.window=7, robust=FALSE, 
    method=c("ets","arima", "naive", "rwdrift"), etsmodel="ZZN",
    level=c(80,95), fan=FALSE, lambda=NULL, xreg=NULL, newxreg=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!="ets", 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" or the span (in lags) of the loess window for seasonal extraction.
robust
If TRUE, robust fitting will used in the loess procedure within stl.
xreg
Historical regressors to be used in auto.arima().
newxreg
Future regressors to be used in forecast.Arima().
...
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.

Values

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.

See Also

forecast.ets, forecast.Arima.

Examples

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

Author(s)

Rob J Hyndman

Documentation reproduced from package forecast, version 5.1. License: GPL (>= 2)