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A Criterion for Local Model Selection

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  • G. Avlogiaris

    (University of Ioannina)

  • A. C. Micheas

    (University of Missouri)

  • K. Zografos

    (University of Ioannina)

Abstract

In this paper, we introduce a class of local divergences between two probability distributions and illustrate its usefulness in model selection. Explicit expressions of the proposed local divergences are derived when the underlying distributions are members of the exponential family of distributions or they are described by multivariate normal models. In addition, a local model selection criterion, termed the local divergence information criterion (LDiv.IC), is proposed. Simulations and applications are presented in order to study and exemplify the performance of the proposed criterion.

Suggested Citation

  • G. Avlogiaris & A. C. Micheas & K. Zografos, 2019. "A Criterion for Local Model Selection," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 406-444, December.
    • Handle: RePEc:spr:sankha:v:81:y:2019:i:2:d:10.1007_s13171-018-0126-x
    DOI: 10.1007/s13171-018-0126-x
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    References listed on IDEAS

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