Final_1.pdf

yt=et+a 1 yt–1+a 2 yt–2+...+apyt–p (2.8)

It is, however, important to bear in mind that the generalized AR series
is generated from a white noise series using linear combinations of past
realizations.

The General ARMA Process

The AR(p) and MA(q) models can be mixed to form an ARMA(p, q) model.
By extrapolation it is easy to see that the generation rule for an ARMA (p, q)
process is given as

Time Series 21

FIGURE 2.3A AR(1) Series.

10 30 50 70 90

–4

–2

0

2

4

FIGURE 2.3B AR(1) Series ACF.

0510 15 20

Lag

–0.2

–0.0

0.2

0.4

0.6

0.8

1.0

Auto Correlation