• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.397-404
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• 1999

For two-dimensional causal spatial autoregressive processes, we propose and illustrate a method for determining asymptotic simultaneous confidence regions using Yule-Walker, unbiased Yule-Walker and least squres estimators. The spectral density for first-order spatial autoregressive model are looked at in more detail. Finite sample properties based on simulation study we also presented.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.10
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• pp.848-855
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• 1989

The asymptotic properties of the Overdetermined Yule-Walker (OYW) estimators were studied. A formula was derived for the asymptotic covariance matrix of the estimation errors. It verified the experimentally observed fact that the frequency estimation accuracy is generally improved as the number of Yule-Walker equations is increased. The asymptotic estimation accuracies of the OYW method were compared with the Cramer-Rao low bound.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.239-248
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• 1994

The Yule-Walker estimator and the approximate conditional least squares estimator of the parameter of the EARMA(1, 1) model are obtained. These two estimators are compared by simulation study. It is shown that the approximate conditional least squares estimator is better in the sense of the mean square error than the Yul-Walker estimator.