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The Deviance Information Criterion in Comparison of Normal Mixing Models

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  • Thomas Fung
  • Joanna J.J. Wang
  • Eugene Seneta

Abstract

type="main" xml:id="insr12063-abs-0001"> Model selection from several non-nested models by using the deviance information criterion within Bayesian inference Using Gibbs Sampling (BUGS) software needs to be treated with caution. This is particularly important if one can specify a model in various mixing representations, as for the normal variance-mean mixing distribution occurring in financial contexts. We propose a procedure to compare goodness of fit of several non-nested models, which uses BUGS software in part.

Suggested Citation

  • Thomas Fung & Joanna J.J. Wang & Eugene Seneta, 2014. "The Deviance Information Criterion in Comparison of Normal Mixing Models," International Statistical Review, International Statistical Institute, vol. 82(3), pages 411-421, December.
    • Handle: RePEc:bla:istatr:v:82:y:2014:i:3:p:411-421
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    File URL: http://hdl.handle.net/10.1111/insr.12063
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    References listed on IDEAS

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    1. Richard Finlay & Eugene Seneta, 2008. "Stationary‐Increment Variance‐Gamma and t Models: Simulation and Parameter Estimation," International Statistical Review, International Statistical Institute, vol. 76(2), pages 167-186, August.
    2. Yong Li & Zeng Tao & Jun Yu, "undated". "Robust Deviance Information Criterion for Latent Variable Models," Working Papers CoFie-04-2012, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    3. Elisa Luciano & Wim Schoutens, 2006. "A multivariate jump-driven financial asset model," Quantitative Finance, Taylor & Francis Journals, vol. 6(5), pages 385-402.
    4. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258.
    5. Thomas Fung & Eugene Seneta, 2010. "Modelling and Estimation for Bivariate Financial Returns," International Statistical Review, International Statistical Institute, vol. 78(1), pages 117-133, April.
    6. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    7. Branco, Márcia D. & Dey, Dipak K., 2001. "A General Class of Multivariate Skew-Elliptical Distributions," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 99-113, October.
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    Cited by:

    1. Zhang, Ping & Wang, Jianwen & Atkinson, Peter M., 2019. "Identifying the spatio-temporal risk variability of avian influenza A H7N9 in China," Ecological Modelling, Elsevier, vol. 414(C).

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