On maximum-likelihood estimation of difference equation parameters

Author

Stoica, Petre ; Viberg, Mats

Author_Institution

Syst. & Control Group, Uppsala Univ., Sweden

Volume

43

Issue

8

fYear

1995

fDate

8/1/1995 12:00:00 AM

Firstpage

2035

Lastpage

2037

Abstract

The article is prompted by a paper written by Liang, Wilkes and Cadzow (see ibid., vol.41, p. 3003-3009, 1993) which discussed the maximum likelihood (ML) estimation of difference equation parameters in a flawed manner. The correct ML parameter estimate is derived herein by means of a high-level argument based on the invariance principle as well as by a direct calculation. Contrary to what is suggested in the aforementioned paper, all ML-based order estimation procedures (such as AIC or GAIC rules) yield results that do not depend on the normalizing constraint imposed on the parameter vector

Keywords

difference equations; maximum likelihood estimation; signal processing; ML parameter estimate; ML-based order estimation; difference equation parameters; direct calculation; invariance principle; maximum-likelihood estimation; normalizing constraint; parameter vector; signal processing; Automatic control; Control systems; Councils; Difference equations; Jacobian matrices; Maximum likelihood estimation; Parameter estimation; Random variables; State estimation;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.403375

Filename

403375