Returns forecasts and other information for univariate ARIMA models.

# 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, ...)

object | An object of class " |
---|---|

h | Number of periods for forecasting. If |

level | Confidence level for prediction intervals. |

fan | If |

lambda | Box-Cox transformation parameter. If |

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. |

... | Other arguments. |

xreg | Future values of an regression variables (for class |

bootstrap | If |

npaths | Number of sample paths used in computing simulated prediction
intervals when |

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:

A list containing information about the fitted model

The name of the forecasting method as a character string

Point forecasts as a time series

Lower limits for prediction intervals

Upper limits for prediction intervals

The confidence values associated with the prediction intervals

The original time series
(either `object`

itself or the time series used to create the model
stored as `object`

).

Residuals from the fitted model. That is x minus fitted values.

Fitted values (one-step forecasts)

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).

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`

.

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