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,
...
)
An object of class "Arima
", "ar
" or
"fracdiff
". Usually the result of a call to
arima
, auto.arima
,
ar
, arfima
or
fracdiff
.
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
.
Confidence level for prediction intervals.
If TRUE
, level is set to seq(51,99,by=3)
. This is
suitable for fan plots.
Box-Cox transformation parameter. If lambda="auto"
,
then a transformation is automatically selected using BoxCox.lambda
.
The transformation is ignored if NULL. Otherwise,
data transformed before model is estimated.
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.
Future values of an regression variables (for class Arima
objects only). A numerical vector or matrix of external regressors; it should not be a data frame.
If TRUE
, then prediction intervals computed using
simulation with resampled errors.
Number of sample paths used in computing simulated prediction
intervals when bootstrap=TRUE
.
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
.
# 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))
# }
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