% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/arfima.R, R/arima.R
\name{forecast.fracdiff}
\alias{forecast.fracdiff}
\alias{forecast.Arima}
\alias{forecast.forecast_ARIMA}
\alias{forecast.ar}
\title{Forecasting using ARIMA or ARFIMA models}
\usage{
\method{forecast}{fracdiff}(
  object,
  h = 10,
  level = c(80, 95),
  fan = FALSE,
  lambda = object$lambda,
  biasadj = NULL,
  ...
)

\method{forecast}{Arima}(
  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,
  ...
)

\method{forecast}{ar}(
  object,
  h = 10,
  level = c(80, 95),
  fan = FALSE,
  lambda = NULL,
  bootstrap = FALSE,
  npaths = 5000,
  biasadj = FALSE,
  ...
)
}
\arguments{
\item{object}{An object of class "\code{Arima}", "\code{ar}" or
"\code{fracdiff}". Usually the result of a call to
\code{\link[stats]{arima}}, \code{\link{auto.arima}},
\code{\link[stats]{ar}}, \code{\link{arfima}} or
\code{\link[fracdiff]{fracdiff}}.}

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

\item{level}{Confidence level for prediction intervals.}

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

\item{lambda}{Box-Cox transformation parameter. If \code{lambda="auto"},
then a transformation is automatically selected using \code{BoxCox.lambda}.
The transformation is ignored if NULL. Otherwise,
data transformed before model is estimated.}

\item{biasadj}{Use adjusted back-transformed mean for Box-Cox
transformations. If transformed data is used to produce forecasts and fitted values,
a regular back transformation will result in median forecasts. If biasadj is TRUE,
an adjustment will be made to produce mean forecasts and fitted values.}

\item{...}{Other arguments.}

\item{xreg}{Future values of an regression variables (for class \code{Arima}
objects only). A numerical vector or matrix of external regressors; it should not be a data frame.}

\item{bootstrap}{If \code{TRUE}, then prediction intervals computed using
simulation with resampled errors.}

\item{npaths}{Number of sample paths used in computing simulated prediction
intervals when \code{bootstrap=TRUE}.}
}
\value{
An object of class "\code{forecast}".

The function \code{summary} is used to obtain and print a summary of the
results, while the function \code{plot} produces a plot of the forecasts and
prediction intervals.

The generic accessor functions \code{fitted.values} and \code{residuals}
extract useful features of the value returned by \code{forecast.Arima}.

An object of class "\code{forecast}" is a list containing at least the
following elements: \item{model}{A list containing information about the
fitted model} \item{method}{The name of the forecasting method as a
character string} \item{mean}{Point forecasts as a time series}
\item{lower}{Lower limits for prediction intervals} \item{upper}{Upper
limits for prediction intervals} \item{level}{The confidence values
associated with the prediction intervals} \item{x}{The original time series
(either \code{object} itself or the time series used to create the model
stored as \code{object}).} \item{residuals}{Residuals from the fitted model.
That is x minus fitted values.} \item{fitted}{Fitted values (one-step
forecasts)}
}
\description{
Returns forecasts and other information for univariate ARIMA models.
}
\details{
For \code{Arima} or \code{ar} objects, the function calls
\code{\link[stats]{predict.Arima}} or \code{\link[stats]{predict.ar}} and
constructs an object of class "\code{forecast}" from the results. For
\code{fracdiff} objects, the calculations are all done within
\code{\link{forecast.fracdiff}} using the equations given by Peiris and
Perera (1988).
}
\examples{
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))

}
\references{
Peiris, M. & Perera, B. (1988), On prediction with fractionally
differenced ARIMA models, \emph{Journal of Time Series Analysis},
\bold{9}(3), 215-220.
}
\seealso{
\code{\link[stats]{predict.Arima}},
\code{\link[stats]{predict.ar}}, \code{\link{auto.arima}},
\code{\link{Arima}}, \code{\link[stats]{arima}}, \code{\link[stats]{ar}},
\code{\link{arfima}}.
}
\author{
Rob J Hyndman
}
\keyword{ts}