Summary
ARMA process covariances.
Declaration
Function ARMAKappa(gamma, maacvf: TVec; i, j: Integer; Phi, Theta: TVec): TSample;
| Parameter | Description |
|---|---|
| gamma | Time series ACVF. |
| maacvf | The ACVF of a MA part of the model. |
Description
Calculates ARMA (p,q) process covariances. For ARMa process, covariances are defined as:
where gamma is time series autocovariance function, sigma^2 is estimated white noise, m=max(p,q) and phi, theta are AR and MA coefficients.
Categories
ARMA and ARIMA routines| See Also |
|---|
| ARMAAcf |
Declaration
Procedure ARMAKappa(Data: TVec; Phi, Theta: TVec; Cov: TMtx; KappaSize: Integer);
Description
Calculate necessary covariances for ARMA(p,q) process up to kappa(KappaSize,KappaSize)| Copyright 2008 Dew Research |