Forecast from ARIMA fits
Forecast from models fitted by
## S3 method for class 'Arima': predict(object, n.ahead = 1, newxreg = NULL, se.fit = TRUE, \dots)
- The result of an
- The number of steps ahead for which prediction is required.
- New values of
xregto be used for prediction. Must have at least
- Logical: should standard errors of prediction be returned?
- arguments passed to or from other methods.
Finite-history prediction is used, via
This is only statistically efficient if the MA part of the fit is
predict.Arima will give a warning for
non-invertible MA models.
The standard errors of prediction exclude the uncertainty in the
estimation of the ARMA model and the regression coefficients.
According to Harvey (1993, pp.
- A time series of predictions, or if
se.fit = TRUE, a list with components
pred, the predictions, and
se, the estimated standard errors. Both components are time series.
Durbin, J. and Koopman, S. J. (2001) Time Series Analysis by State Space Methods. Oxford University Press.
Harvey, A. C. and McKenzie, C. R. (1982) Algorithm AS182. An algorithm for finite sample prediction from ARIMA processes. Applied Statistics 31, 180--187.
Harvey, A. C. (1993) Time Series Models, 2nd Edition, Harvester Wheatsheaf, sections 3.3 and 4.4.
od <- options(digits = 5) # avoid too much spurious accuracy predict(arima(lh, order = c(3,0,0)), n.ahead = 12) (fit <- arima(USAccDeaths, order = c(0,1,1), seasonal = list(order = c(0,1,1)))) predict(fit, n.ahead = 6) options(od)