Autoregressive spectral estimation in additive noise

The estimation of the spectral density of a discrete-time stationary Gaussian autoregressive process AR (p) from a finite set of noise observations is considered. A modified spectral estimator based on the high-order Yule-Walker equations is considered. Joint asymptotic normality of this spectral estimator is established; a precise asymptotic expression for the covariance matrix of the limiting distribution is obtained. The special case of AR(1) plus noise is considered in some detail.<
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