Estimate the coefficients of an ARIMA model
"ARIMA modeling" treats the given signal y as an Auto-Regressive
Integrated Moving Average (ARIMA) process according to
with the input data x passed through a difference filter D times.
This difference filter is given by
where N denotes the length of x.
"ARIMA modeling" estimates its model coefficients of the given order and
returns the residual r, i.e. the estimation error signal.
Input parameters are
- order P of the AR process,
- order Q of the MA process and
- integral order D.
The AR and MA coefficients of the estimated model will appear in the
r = ARIMAmodel(y,P,Q,D);
ARIMAX modeling, ARMA model order,
ARMA modeling, ARMA simulation,
ARMA spectral density, ARMAX modeling,
ARMAX simulation, NAR modeling,
Ljung , Conover , Graybill
, Hollander/Wolfe .