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Independent Additive Weighted Bias Distributions and Associated Goodness-of-Fit Tests

In: Recent Advances in Econometrics and Statistics

Author

Listed:
  • Bruno Ebner

    (Karlsruhe Institute of Technology (KIT), Institute of Stochastics)

  • Yvik Swan

    (Université libre de Bruxelles, Département de Mathématique)

Abstract

We use a Stein identity to define a new class of distributions which we call “independent additive weighted bias distributions.” We investigate related L 2 $$L^2$$ -type discrepancy measures, empirical versions of which not only encompass traditional ODE-based procedures but also offer novel methods for conducting goodness-of-fit tests in composite hypothesis testing problems. We determine critical values for these new procedures using a parametric bootstrap approach and evaluate their power through Monte Carlo simulations. As an illustration, we apply these procedures to examine the compatibility of two real datasets with a compound Poisson gamma distribution.

Suggested Citation

  • Bruno Ebner & Yvik Swan, 2024. "Independent Additive Weighted Bias Distributions and Associated Goodness-of-Fit Tests," Springer Books, in: Matteo Barigozzi & Siegfried Hörmann & Davy Paindaveine (ed.), Recent Advances in Econometrics and Statistics, pages 511-532, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-61853-6_26
    DOI: 10.1007/978-3-031-61853-6_26
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