A comparison of two linear methods of estimating the parameters of ARMA models

Author

Li, Shiping ; Zhu, Yao ; Dickinson, Bradley W.

Author_Institution

Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA

Volume

34

Issue

8

fYear

1989

fDate

8/1/1989 12:00:00 AM

Firstpage

915

Lastpage

917

Abstract

A finite-order stationary and minimum-phase ARMA (autoregressive moving-average) (p,q) model is equivalent to an infinite-order AR (autoregressive) model. Two methods of estimating the parameters of the ARMA (p,q) model by solving only linear equations are based on or closely related to this equivalence relation. One method was derived directly from the equivalence relation by D. Graupe et al. (ibid., vol.AC-20, p.104-107, Feb. 1975). The other was derived by S. Li and B.W. Dickinson (ibid., vol.AC-31, p.275-278, Mar. 1986 and IEEE Trans. Acoust. Speech Signal Process., vol.ASSP-36, p.502-512, Apr. 1988) based on an iterated least-squares regression approach. The end results bear close resemblance to those of Graupe et al. The two methods are compared, and ways to improve the parameter estimates are suggested

Keywords

iterative methods; least squares approximations; parameter estimation; time series; (p,q) model; ARMA models; equivalence relation; finite-order stationary; iterated least-squares regression approach; iterative methods; least squares approximations; linear equations; linear methods; minimum-phase; parameter estimation; time series; Delay; Least squares approximation; Nonlinear equations; Parameter estimation; Phase estimation; Transforms;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.29444

Filename

29444