Outlier evaluation for the bilinear time series model.

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 thres...

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Main Authors: Mohamed, I.B., Ismail, M.I.
Format: Conference or Workshop Item
Language:en
Published: 2008
Subjects:
Online Access:http://eprints.um.edu.my/10366/1/Outlier_evaluation_for_the_bilinear_time_series_model.pdf
http://eprints.um.edu.my/10366/
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author Mohamed, I.B.
Ismail, M.I.
author_facet Mohamed, I.B.
Ismail, M.I.
author_sort Mohamed, I.B.
building UM Library
collection Institutional Repository
content_provider Universiti Malaya
content_source UM Research Repository
continent Asia
country Malaysia
description 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.
format Conference or Workshop Item
id my.um.eprints-10366
institution Universiti Malaya
language en
publishDate 2008
record_format eprints
spelling my.um.eprints-103662014-10-28T05:59:12Z http://eprints.um.edu.my/10366/ Outlier evaluation for the bilinear time series model. Mohamed, I.B. Ismail, M.I. QA Mathematics 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. 2008 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.um.edu.my/10366/1/Outlier_evaluation_for_the_bilinear_time_series_model.pdf 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)
spellingShingle QA Mathematics
Mohamed, I.B.
Ismail, M.I.
Outlier evaluation for the bilinear time series model.
title Outlier evaluation for the bilinear time series model.
title_full Outlier evaluation for the bilinear time series model.
title_fullStr Outlier evaluation for the bilinear time series model.
title_full_unstemmed Outlier evaluation for the bilinear time series model.
title_short Outlier evaluation for the bilinear time series model.
title_sort outlier evaluation for the bilinear time series model.
topic QA Mathematics
url http://eprints.um.edu.my/10366/1/Outlier_evaluation_for_the_bilinear_time_series_model.pdf
http://eprints.um.edu.my/10366/
url_provider http://eprints.um.edu.my/