Improvement on additive outlier detection procedure in bilinear model

Ismail, Mohd Isfahani and Mohamed, Ibrahim and Yahya, Mohd Sahar (2008) Improvement on additive outlier detection procedure in bilinear model. Malaysian Journal of Science, 27 (2). pp. 107-113. ISSN 1394-3065,

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This paper considers the problem of outlier detection in bilinear time series data; with special focus on two most basic models BL(1,0,1,1) and BL(1,1,1,1). The formulation of effect of additive outlier on the observations and residuals has been developed and the least squares estimator of the outlier effect has been derived. Consequently, an outlier detection procedure employing bootstrapping method to estimate the variance of the estimator has been proposed. In this paper, we propose to use the mean absolute deviance and trimmed mean methods to improve the performances of the procedure. Using simulation works, we show that trimmed method has successfully improved the performance. Subsequently the procedure is applied to a real data set.

Item Type: Article
Uncontrolled Keywords: Additive outlier; Bilinear; Bootstrapping; Least squares method; Rainfall data
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Centre for Foundation Studies in Science
Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 11 Dec 2020 08:30
Last Modified: 11 Dec 2020 08:30

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