forecast (version 7.3)

forecast.Arima: Forecasting using ARIMA or ARFIMA models

Description

Returns forecasts and other information for univariate ARIMA models.

Usage

"forecast"(object, h=ifelse(object$arma[5]>1,2*object$arma[5],10), level=c(80,95), fan=FALSE, xreg=NULL, lambda=object$lambda,  bootstrap=FALSE, npaths=5000, biasadj=FALSE, ...)
"forecast"(object, h=10, level=c(80,95), fan=FALSE, lambda=NULL,  bootstrap=FALSE, npaths=5000, biasadj=FALSE, ...)
"forecast"(object, h=10, level=c(80,95), fan=FALSE, lambda=object$lambda, biasadj=FALSE, ...)

Arguments

object

An object of class "Arima", "ar" or "fracdiff". Usually the result of a call to arima, auto.arima, ar, arfima or fracdiff.

h

Number of periods for forecasting. If xreg is used, h is ignored and the number of forecast periods is set to the number of rows of xreg.

level

Confidence level for prediction intervals.

fan

If TRUE, level is set to seq(51,99,by=3). This is suitable for fan plots.

xreg

Future values of an regression variables (for class Arima objects only).

lambda

Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.

biasadj

Use adjusted back-transformed mean for Box-Cox transformations. If TRUE, point forecasts and fitted values are mean forecast. Otherwise, these points can be considered the median of the forecast densities.

bootstrap

If TRUE, then prediction intervals computed using simulation with resampled errors.

npaths

Number of sample paths used in computing simulated prediction intervals when bootstrap=TRUE.

...

Other arguments.

Value

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.Arima.An object of class "forecast" is a list containing at least the following elements: " is a list containing at least the following elements:

Details

For Arima or ar objects, the function calls predict.Arima or predict.ar and constructs an object of class "forecast" from the results. For fracdiff objects, the calculations are all done within forecast.fracdiff using the equations given by Peiris and Perera (1988).

References

Peiris, M. & Perera, B. (1988), On prediction with fractionally differenced ARIMA models, Journal of Time Series Analysis, 9(3), 215-220.

See Also

predict.Arima, predict.ar, auto.arima, Arima, arima, ar, arfima.

Examples

plot(forecast(fit))

library(fracdiff)
x <- fracdiff.sim( 100, ma=-.4, d=.3)$series
fit <- arfima(x)
plot(forecast(fit,h=30))