Title :
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
fDate :
8/1/1989 12:00:00 AM
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;
Journal_Title :
Automatic Control, IEEE Transactions on
