Detecting an innovative outlier in a set of time series

Caroni, C; Karioti, V

dc.contributor.author	Caroni, C	en
dc.contributor.author	Karioti, V	en
dc.date.accessioned	2014-03-01T01:20:10Z
dc.date.available	2014-03-01T01:20:10Z
dc.date.issued	2004	en
dc.identifier.issn	0167-9473	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15852
dc.subject	Autoregressive model	en
dc.subject	Innovative outliers	en
dc.subject	Time series	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Statistics & Probability	en
dc.subject.other	Computer simulation	en
dc.subject.other	Correlation methods	en
dc.subject.other	Mathematical models	en
dc.subject.other	Maximum likelihood estimation	en
dc.subject.other	Random processes	en
dc.subject.other	Regression analysis	en
dc.subject.other	Table lookup	en
dc.subject.other	Time series analysis	en
dc.subject.other	Heteroscedastic time series	en
dc.subject.other	Innovative outliers	en
dc.subject.other	Random effects	en
dc.subject.other	Data reduction	en
dc.subject.other	statistical analysis	en
dc.title	Detecting an innovative outlier in a set of time series	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.csda.2003.09.004	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.csda.2003.09.004	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	Tests for an innovative outlier affecting every member of a set of autoregressive time series at the same time point are developed. In one model, the outliers are represented as independent random effects; likelihood ratio tests are derived for this case and simulated critical values are tabulated. In a second model, assuming that the size of the outlier is the same in each series, a standard regression framework can be used and correlations between the series are introduced. Simulation studies show that approximate critical values obtained from the chi(1)(2) distribution work well for heteroscedastic independent series and for the case of equal correlations between each pair of series. (C) 2003 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Computational Statistics and Data Analysis	en
dc.identifier.doi	10.1016/j.csda.2003.09.004	en
dc.identifier.isi	ISI:000222135000010	en
dc.identifier.volume	46	en
dc.identifier.issue	3	en
dc.identifier.spage	561	en
dc.identifier.epage	570	en