sarima.for {astsa} | R Documentation |
ARIMA forecasting - this is a wrapper for R's predict.Arima
.
sarima.for(xdata, n.ahead, p, d, q, P = 0, D = 0, Q = 0, S = -1, tol = sqrt(.Machine$double.eps), no.constant = FALSE, plot.all=FALSE, xreg = NULL, newxreg = NULL, fixed=NULL)
xdata |
univariate time series |
n.ahead |
forecast horizon (number of periods) |
p |
AR order |
d |
difference order |
q |
MA order |
P |
SAR order; use only for seasonal models |
D |
seasonal difference; use only for seasonal models |
Q |
SMA order; use only for seasonal models |
S |
seasonal period; use only for seasonal models |
tol |
controls the relative tolerance (reltol) used to assess convergence. The default is |
no.constant |
controls whether or not a constant is included in the model. If |
plot.all |
if TRUE, all the data are plotted in the graphic; otherwise, only the last 100 observations are plotted in the graphic. |
xreg |
Optionally, a vector or matrix of external regressors, which must have the same number of rows as the series. If this
is used, |
newxreg |
New values of |
fixed |
optional numeric vector of the same length as the total number of parameters. If supplied, only parameters corresponding to NA entries will be estimated. |
For example, sarima.for(x,5,1,0,1)
will forecast five time points ahead for an ARMA(1,1) fit to x. The output prints the forecasts and the standard errors of the forecasts, and supplies a graphic of the forecast with +/- 1 and 2 prediction error bounds.
pred |
the forecasts |
se |
the prediction (standard) errors |
http://www.stat.pitt.edu/stoffer/tsa4/ and http://www.stat.pitt.edu/stoffer/tsda/
sarima.for(log(AirPassengers),12,0,1,1,0,1,1,12) # with regressors: nummy = length(soi) n.ahead = 24 nureg = time(soi)[nummy] + seq(1,n.ahead)/12 sarima.for(soi,n.ahead,2,0,0,2,0,0,12, xreg=time(soi), newxreg=nureg)