forecast.fracdiff | R Documentation |
Returns forecasts and other information for univariate ARIMA models.
## S3 method for class 'fracdiff'
forecast(
object,
h = 10,
level = c(80, 95),
fan = FALSE,
lambda = object$lambda,
biasadj = NULL,
...
)
## S3 method for class 'Arima'
forecast(
object,
h = ifelse(object$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 class '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 |
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).
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 |
residuals |
Residuals from the fitted model. That is x minus fitted values. |
fitted |
Fitted values (one-step forecasts) |
Rob J Hyndman
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
.
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))
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