```
"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, ...)
```

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.

`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:`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).
`predict.Arima`

, `predict.ar`

, `auto.arima`

, `Arima`

,
`arima`

, `ar`

, `arfima`

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

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