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E?ciency of the V-fold model selection for localized bases

Author

Listed:
  • Fabien Navarro

    (CREST;ENSAI)

  • Adrien Saumard

    (CREST;ENSAI)

Abstract

Many interesting functional bases, such as piecewise polynomials or wavelets, are examples of localized bases. We investigate the optimality of V-fold cross-validation and a variant called V-fold penalization in the context of the selection of linear models generated by localized bases in a heteroscedastic framework. It appears that while V-fold cross-validation is not asymptotically optimal when V is ?xed, the V-fold penalization procedure is optimal. Simulation studies are also presented.

Suggested Citation

  • Fabien Navarro & Adrien Saumard, 2017. "E?ciency of the V-fold model selection for localized bases," Working Papers 2017-65, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2017-65
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    References listed on IDEAS

    as
    1. Fabien Navarro & Adrien Saumard, 2017. "Slope heuristics and V-Fold model selection in heteroscedastic regression using strongly localized bases," Working Papers 2017-67, Center for Research in Economics and Statistics.
    2. Cai, T. Tony & Brown, Lawrence D., 1999. "Wavelet estimation for samples with random uniform design," Statistics & Probability Letters, Elsevier, vol. 42(3), pages 313-321, April.
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