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A novel method for estimating the parameter of a Gaussian AR(1) process with additive outliers

Author(s): Wararit Panichkitkosolkul

Journal: Maejo International Journal of Science and Technology
ISSN 1905-7873

Volume: 5;
Issue: 01;
Start page: 58;
Date: 2011;
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Keywords: parameter estimation | AR(1) process | recursive median | trimmed mean | additive outliers

A novel estimator for a Gaussian first-order autoregressive [AR(1)] process with additive outliers is presented. A recursive median adjustment based on an -trimmed mean was applied to the weighted symmetric estimator. The following estimators were considered: the weighted symmetric estimator ( ), the recursive-mean-adjusted weighted symmetric estimator ( ), the recursive-median-adjusted weighted symmetric estimator ( ), and the weighted symmetric estimator using adjusted recursive median based on the -trimmed mean ( ). Using Monte Carlo simulations, the mean square errors (MSE) of the estimators were compared. Simulation results showed that the proposed estimator, , provided a smaller MSE than those from , and for almost all situations.
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