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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 |
Download |
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 Journal of Science, 2010; 37(1): 14-20. |
SDGs |
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