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Robust model selection in regression via weighted likelihood methodology

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  • Agostinelli, Claudio

Abstract

Robust model selection procedures are introduced as a robust modification of the Akaike information criterion (AIC) and Mallows Cp. These extensions are based on the weighted likelihood methodology. When the model is correctly specified, these robust criteria are asymptotically equivalent to the classical ones under mild conditions. Robustness properties and the performance of the procedures are illustrated with examples and Monte Carlo simulations.

Suggested Citation

  • Agostinelli, Claudio, 2002. "Robust model selection in regression via weighted likelihood methodology," Statistics & Probability Letters, Elsevier, vol. 56(3), pages 289-300, February.
    • Handle: RePEc:eee:stapro:v:56:y:2002:i:3:p:289-300
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    References listed on IDEAS

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    1. Agostinelli, Claudio & Markatou, Marianthi, 1998. "A one-step robust estimator for regression based on the weighted likelihood reweighting scheme," Statistics & Probability Letters, Elsevier, vol. 37(4), pages 341-350, March.
    2. Ronchetti, Elvezio, 1985. "Robust model selection in regression," Statistics & Probability Letters, Elsevier, vol. 3(1), pages 21-23, February.
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    Cited by:

    1. Riani, Marco & Atkinson, Anthony C., 2010. "Robust model selection with flexible trimming," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3300-3312, December.
    2. Suman Majumder & Adhidev Biswas & Tania Roy & Subir Kumar Bhandari & Ayanendranath Basu, 2021. "Statistical inference based on a new weighted likelihood approach," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(1), pages 97-120, January.
    3. Claudio Agostinelli & Luca Greco, 2018. "Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(4), pages 609-619, December.
    4. Luca Greco & Antonio Lucadamo & Claudio Agostinelli, 2021. "Weighted likelihood latent class linear regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 711-746, June.
    5. Luca Greco, 2022. "Robust fitting of mixtures of GLMs by weighted likelihood," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 25-48, March.
    6. C. Agostinelli, 2002. "Robust stepwise regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(6), pages 825-840.
    7. Taylor, James W., 2008. "Exponentially weighted information criteria for selecting among forecasting models," International Journal of Forecasting, Elsevier, vol. 24(3), pages 513-524.
    8. Schomaker, Michael & Wan, Alan T.K. & Heumann, Christian, 2010. "Frequentist Model Averaging with missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3336-3347, December.
    9. Salibian-Barrera, Matias & Van Aelst, Stefan, 2008. "Robust model selection using fast and robust bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5121-5135, August.

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