Sufficient reduction in multivariate surveillance

Marianne Frisén, Eva Andersson (eva.andersson@statistics.gu.se) and Linus Schiöler
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Eva Andersson: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG
Linus Schiöler: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG

No 2009:2, Research Reports from University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law

Abstract: The relation between change points in multivariate surveillance is important but seldom considered. The sufficiency principle is here used to clarify the structure of some problems, to find efficient methods, and to determine appropriate evaluation metrics. We study processes where the changes occur simultaneously or with known time lags. The surveillance of spatial data is one example where known time lags can be of interest. A general version of a theorem for the sufficient reduction of processes that change with known time lags is given. A simulation study illustrates the benefits or the methods based on the sufficient statistics.

Keywords: change-points; exponential family; MEWMA; monitoring; inference principles (search for similar items in EconPapers)
JEL-codes: C10 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2009-08-31
New Economics Papers: this item is included in nep-ecm
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Published as Frisén, Marianne, Eva Andersson and Linus Schiöler, 'Sufficient reduction in multivariate surveillance' in Communications in Statistics. Theory and Methods, 2011, pages 1821-1838.

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Persistent link: https://EconPapers.repec.org/RePEc:hhs:gunsru:2009_002

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