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Generalization error for Tweedie models: decomposition and error reduction with bagging

Author

Listed:
  • Denuit, Michel

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Trufin, Julien

    (Université Libre de Bruxelles)

Abstract

Wüthrich and Buser (DOI:10.2139/ssrn.2870308, 2020) studied the generalization error for Poisson regression models. This short note aims to extend their results to the Tweedie family of distributions, to which the Poisson law belongs. In case of bagging, a new condition emerges that becomes increasingly binding with the power parameter involved in the Tweedie variance function.

Suggested Citation

  • Denuit, Michel & Trufin, Julien, 2021. "Generalization error for Tweedie models: decomposition and error reduction with bagging," LIDAM Reprints ISBA 2021025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2021025
    DOI: https://doi.org/10.1007/s13385-021-00265-2
    Note: In: European Actuarial Journal, 2021, vol. 11, p. 325-331
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    Cited by:

    1. Alicja Wolny-Dominiak & Tomasz Żądło, 2021. "The Measures of Accuracy of Claim Frequency Credibility Predictor," Sustainability, MDPI, vol. 13(21), pages 1-13, October.

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