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Decomposability and selection of graphical models for multivariate time series

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  • Roland Fried

Abstract

We derive conditions for decomposition and collapsibility of graphical interaction models for multivariate time series. These properties enable us to perform stepwise model selection under certain restrictions. For illustration, we apply the results to a multivariate time series describing the haemodynamic system as monitored in intensive care. Copyright Biometrika Trust 2003, Oxford University Press.

Suggested Citation

  • Roland Fried, 2003. "Decomposability and selection of graphical models for multivariate time series," Biometrika, Biometrika Trust, vol. 90(2), pages 251-267, June.
  • Handle: RePEc:oup:biomet:v:90:y:2003:i:2:p:251-267
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    Cited by:

    1. Eichler, Michael, 2008. "Testing nonparametric and semiparametric hypotheses in vector stationary processes," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 968-1009, May.
    2. Abdelwahab Allali & Amor Oueslati & Abdelwahed Trabelsi, 2011. "Detection of Information Flow in Major International Financial Markets by Interactivity Network Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 18(3), pages 319-344, September.
    3. Fried, Roland & Didelez, Vanessa, 2005. "Latent variable analysis and partial correlation graphs for multivariate time series," Statistics & Probability Letters, Elsevier, vol. 73(3), pages 287-296, July.

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