Leave-K-Out Diagnostics In State-Space Models
AbstractThe paper derives an algorithm for computing leave-k-out diagnostics for the detection of patches of outliers for stationary and nonstationary state-space models with regression effects. The algorithm is based on a reverse run of the Kalman filter on the smoothing errors and is both efficient and easy to implement. The US index of industrial production for textiles is used to illustrate the application of the algorithm. Copyright 2003 Blackwell Publishing Ltd.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Time Series Analysis.
Volume (Year): 24 (2003)
Issue (Month): 2 (03)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782
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