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Leave-K-Out Diagnostics In State-Space Models

  • Tommaso Proietti

The 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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Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 24 (2003)
Issue (Month): 2 (03)
Pages: 221-236

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Handle: RePEc:bla:jtsera:v:24:y:2003:i:2:p:221-236
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  1. Sichel, D.E., 1988. "Business Cycle Asymmetry: A Deeper Look," Papers 85, Princeton, Department of Economics - Financial Research Center.
  2. Proietti Tommaso, 1998. "Characterizing Asymmetries in Business Cycles Using Smooth-Transition Structural Time-Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(3), pages 1-18, October.
  3. Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-89, October.
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