Performances test statistics for single outlier detection in bilinear (1,1,1,1) models

An outlier detection procedure for BL(1,1,1,1) model is developed based on the maxima of the test statistics measuring the effects of IO, AO, TC and LC. A simulation study is carried out in order to investigate the sampling properties of the maxima of the outlier test statistics. It is associated wi...

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Main Authors: Zaharim, A., Mohamed, I., Ahmad, I., Abdullah, S., Omar, M.Z.
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Published: 2017
Online Access:http://dspace.uniten.edu.my:8080/jspui/handle/123456789/5308
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-53082017-11-15T02:57:26Z Performances test statistics for single outlier detection in bilinear (1,1,1,1) models Zaharim, A. Mohamed, I. Ahmad, I. Abdullah, S. Omar, M.Z. An outlier detection procedure for BL(1,1,1,1) model is developed based on the maxima of the test statistics measuring the effects of IO, AO, TC and LC. A simulation study is carried out in order to investigate the sampling properties of the maxima of the outlier test statistics. It is associated with the sample size, the type of outlier and the coefficients chosen for BL(1,1,1,1). The results show that, in general, the performance of the detection procedure is good. The outlier detection procedure performs well in detecting AO for large value of ω̂AO. As for IO, the performance of outlier detection procedure is better for model with larger coefficient values. The outlier detection procedure is capable of detecting TC and LC, though the performance is affected if ω is large. 2017-11-15T02:57:26Z 2017-11-15T02:57:26Z 2006 http://dspace.uniten.edu.my:8080/jspui/handle/123456789/5308
institution Universiti Tenaga Nasional
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country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
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description An outlier detection procedure for BL(1,1,1,1) model is developed based on the maxima of the test statistics measuring the effects of IO, AO, TC and LC. A simulation study is carried out in order to investigate the sampling properties of the maxima of the outlier test statistics. It is associated with the sample size, the type of outlier and the coefficients chosen for BL(1,1,1,1). The results show that, in general, the performance of the detection procedure is good. The outlier detection procedure performs well in detecting AO for large value of ω̂AO. As for IO, the performance of outlier detection procedure is better for model with larger coefficient values. The outlier detection procedure is capable of detecting TC and LC, though the performance is affected if ω is large.
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author Zaharim, A.
Mohamed, I.
Ahmad, I.
Abdullah, S.
Omar, M.Z.
spellingShingle Zaharim, A.
Mohamed, I.
Ahmad, I.
Abdullah, S.
Omar, M.Z.
Performances test statistics for single outlier detection in bilinear (1,1,1,1) models
author_facet Zaharim, A.
Mohamed, I.
Ahmad, I.
Abdullah, S.
Omar, M.Z.
author_sort Zaharim, A.
title Performances test statistics for single outlier detection in bilinear (1,1,1,1) models
title_short Performances test statistics for single outlier detection in bilinear (1,1,1,1) models
title_full Performances test statistics for single outlier detection in bilinear (1,1,1,1) models
title_fullStr Performances test statistics for single outlier detection in bilinear (1,1,1,1) models
title_full_unstemmed Performances test statistics for single outlier detection in bilinear (1,1,1,1) models
title_sort performances test statistics for single outlier detection in bilinear (1,1,1,1) models
publishDate 2017
url http://dspace.uniten.edu.my:8080/jspui/handle/123456789/5308
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