期刊名称：Walailak Journal of Science and Technology (WJST)
印刷版ISSN：2228-835X
出版年度：2012
卷号：9
期号：3
页码：255-262
DOI：10.2004/wjst.v9i3.305
语种：English
出版社：Institute of Research and Development, Walailak University.
摘要：Guttman and Tiao [1], and Chang [2] showed that the effect of outliers may cause serious bias in estimating autocorrelations, partial correlations, and autoregressive moving average parameters (cited in Chang et al. [3]). This paper presents a modified weighted symmetric estimator for a Gaussian first-order autoregressive AR(1) model with additive outliers. We apply the recursive median adjustment based on an exponentially weighted moving average (EWMA) to the weighted symmetric estimator of Park and Fuller [4]. We consider the following estimators: the weighted symmetric estimator (), the recursive mean adjusted weighted symmetric estimator () proposed by Niwitpong [5], the recursive median adjusted weighted symmetric estimator () proposed by Panichkitkosolkul [6], and the weighted symmetric estimator using adjusted recursive median based on EWMA (). Using Monte Carlo simulations, we compare the mean square error (MSE) of estimators. Simulation results have shown that the proposed estimator, , provides a MSE lower than those of , and for almost all situations.
