Outlier evaluation for the bilinear time series model.

Mohamed, I.B. and Ismail, M.I. (2008) Outlier evaluation for the bilinear time series model. In: Conference of the Asian Regional Section of the IASC on Computational Statistics and Data Analysis, 5-8 Dec 2008, Yokohama, Japan. (Submitted)

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Abstract

The problem of detecting an outlier and then identifying its type for bilinear time series data is studied. The e®ects of temporary change type of outlier on the observations and residuals for general bilinear processes are considered and the corresponding least-squares measure of the decision threshold is proposed. Due to the complexity of the statistics, we use a bootstrapping method to estimate the mean and standard deviation of the threshold statistics. We look at the ability of the proposed procedure to correctly detect temporary change type of outlier when compared to additive outlier and innovational outlier procedures developed in previous studies. The performances of three bootstrap-based procedures are investigated through simulation studies and shown to be good.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bilinear; Outlier; Least squares method; Bootstrapping; Rainfall data;
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Mr. Mohd Samsul Ismail
Date Deposited: 18 Jul 2014 01:30
Last Modified: 28 Oct 2014 05:59
URI: http://eprints.um.edu.my/id/eprint/10366

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