Title :
Asymptotically optimal estimation of MA and ARMA parameters of non-Gaussian processes from high-order moments
Author :
Friedlander, Benjamin ; Porat, Boaz
Author_Institution :
Signal Process. Technol. Ltd., Palo Alto, CA, USA
fDate :
1/1/1990 12:00:00 AM
Abstract :
A description is given of an asymptotically-minimum-variance algorithm for estimating the MA (moving-average) and ARMA (autoregressive moving-average) parameters of non-Gaussian processes from sample high-order moments. The algorithm uses the statistical properties (covariances and cross covariances) of the sample moments explicitly. A simpler alternative algorithm that requires only linear operations is also presented. The latter algorithm is asymptotically-minimum-variance in the class of weighted least-squares algorithms
Keywords :
parameter estimation; statistics; time series; ARMA parameters; asymptotically optimal estimation; asymptotically-minimum-variance algorithm; autoregressive moving-average; cross covariances; nonGaussian processes; parameter estimation; statistical properties; time series; weighted least-squares algorithms; Additive noise; Electronic switching systems; Gaussian noise; Gaussian processes; H infinity control; Parameter estimation; Parametric statistics; Phase estimation; Signal processing algorithms; Vectors;
Journal_Title :
Automatic Control, IEEE Transactions on
