# forecast.fracdiff

0th

Percentile

##### Forecasting using ARIMA or ARFIMA models

Returns forecasts and other information for univariate ARIMA models.

Keywords
ts
##### Usage
# S3 method for fracdiff
forecast(object, h = 10, level = c(80, 95),
fan = FALSE, lambda = object$lambda, biasadj = NULL, ...)# S3 method for Arima forecast(object, h = ifelse(object$arma[5] > 1, 2 *
object$arma[5], 10), level = c(80, 95), fan = FALSE, xreg = NULL, lambda = object$lambda, bootstrap = FALSE, npaths = 5000,
biasadj = NULL, ...)# S3 method for ar
forecast(object, h = 10, level = c(80, 95), fan = FALSE,
lambda = NULL, bootstrap = FALSE, npaths = 5000, 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.

lambda

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

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. By default, the value is taken from what was used when fitting the model.

...

Other arguments.

xreg

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

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.

##### 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).

##### 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.Arima.

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)

##### References

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

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

##### Aliases
• forecast.fracdiff
• forecast.Arima
• forecast.ar
##### Examples
# NOT RUN {
fit <- Arima(WWWusage,c(3,1,0))
plot(forecast(fit))

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

# }

Documentation reproduced from package forecast, version 8.2, License: GPL-3

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