Title :
On the CRLB for combined model and model-order estimation of stationary stochastic processes
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Callaghan, Australia
Abstract :
This letter is concerned with quantifying the Cramer-Rao lower bound for model-based spectral density estimation in the case of joint model and model-order estimation. In particular, the results here extend previous work by providing closed-form frequency domain expressions that, among other things, highlight the effect of order estimation bias on the total accuracy of model-based spectral density estimation.
Keywords :
autoregressive moving average processes; frequency-domain analysis; maximum likelihood estimation; spectral analysis; ARMA modeling; Cramer-Rao lower bound; autoregressive moving-average; closed-form frequency domain expressions; maximum-likelihood estimation; model-based spectral density estimation; order estimation bias; stationary stochastic processes; Australia Council; Closed-form solution; Computer aided software engineering; Computer science; Frequency domain analysis; Frequency estimation; Maximum likelihood estimation; Parameter estimation; Spectral analysis; Stochastic processes;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2003.821752
