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The connection between cross-validation and Akaike information criterion in a semiparametric family

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  • Heng Peng
  • Hongjia Yan
  • Wenyang Zhang

Abstract

Both Akaike information criterion and cross-validation are important tools in model selection. Stone [(1977), 'An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaikes Criterion', Journal of the Royal Statistical Society, Series B , 39, 44-47] established the equivalence of these two criteria for parametric models. In this paper, we build a similar equivalence for a large semiparametric family.

Suggested Citation

  • Heng Peng & Hongjia Yan & Wenyang Zhang, 2013. "The connection between cross-validation and Akaike information criterion in a semiparametric family," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 475-485, June.
    • Handle: RePEc:taf:gnstxx:v:25:y:2013:i:2:p:475-485
    DOI: 10.1080/10485252.2013.767338
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    Cited by:

    1. Emre Demirkaya & Yang Feng & Pallavi Basu & Jinchi Lv, 2022. "Large-scale model selection in misspecified generalized linear models [Information theory and an extension of the maximum likelihood principle]," Biometrika, Biometrika Trust, vol. 109(1), pages 123-136.

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