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New Estimator for an Unknown Mean Gaussian AR(1) Process with Additive Outliers


Paper Type 
Contributed Paper
Title 
New Estimator for an Unknown Mean Gaussian AR(1) Process with Additive Outliers
Author 
Wararit Panichkitkosolkul
Email 
wararit@mathstat.sci.tu.ac.th
Abstract:
This paper presents a new estimator for an unknown mean Gaussian AR(1) process with additive outliers. We apply the recursive median adjustment to the weighted symmetric estimator of Park and Fuller
[1]. The mean square error (MSE) is derived. Simulation is used to investigate the behavior of this new estimator (ρ^RMD-W) compared to the weighted symmetric estimator (ρ^W) and the recursively mean adjusted weighted symmetric estimator (ρ^R-W) proposed by Niwitpong
[2]. Simulation results have shown that the proposed estimator, ρ^RMD-W  , provides a MSE lower than those of  ρ^W and ρ^R-W for almost all situations.
Start & End Page 
14 - 20
Received Date 
2009-06-14
Revised Date 
Accepted Date 
2009-09-09
Full Text 
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Keyword 
parameter estimation, AR(1) model, recursive median, additive outliers
Volume 
Vol.37 No.1 (JANUARY 2010)
DOI 
Citation 
Panichkitkosolkul W., New Estimator for an Unknown Mean Gaussian AR(1) Process with Additive Outliers, Chiang Mai J. Sci., 2010; 37(1): 14-20.
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