ARMA (Pro.)

mean
is the ARMA model mean (i.e. mu).

sigma
is the standard deviation of the model's residuals.

phi
are the parameters of the AR(p) component model (starting with the lowest lag).

theta
are the parameters of the MA(q) component model (starting with the lowest lag).

1. The underlying model is described here.
2. The number of parameters in the input argument - phi - determines the order of the AR component.
3. The number of parameters in the input argument - theta - determines the order of the MA component.
4. The residuals/innovations standard deviation (i.e. ) should be greater than zero.
5. The ARMA function returns an array of size of p+q+5 in the following order:
   1. 
   2. 
   3. 
   4. 
   5. 
   6. 
   7. 

• Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
• Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740

• Wikipedia - Autoregressive moving average model