Sufficient reduction in multivariate surveillance
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.
|Date of creation:||31 Aug 2009|
|Date of revision:|
|Publication status:||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.|
|Contact details of provider:|| Postal: Statistical Research Unit, University of Gothenburg, Box 640, SE 40530 GÖTEBORG|
Web page: http://www.statistics.gu.se/
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