Title :
On maximum-likelihood estimation of difference equation parameters
Author :
Stoica, Petre ; Viberg, Mats
Author_Institution :
Syst. & Control Group, Uppsala Univ., Sweden
fDate :
8/1/1995 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
