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Statistical inference based on weighted divergence measures with simulations and applications

Author

Listed:
  • Thomas Gkelsinis

    (Université de Rouen-Normandie)

  • Alex Karagrigoriou

    (University of the Aegean)

  • Vlad Stefan Barbu

    (Université de Rouen-Normandie)

Abstract

In this paper we propose the Directed Goodness of Fit (DGoF) test and the Directed test of Homogeneity (DHom). These types of tests are constructed based on a particular type of discrepancy measures called weighted (or directed) divergences. These measures allow the researcher to focus on specific subsets of the support without, at the same time, losing the information of the others. The performance of the proposed tests examined for a variety of distributions via extensive Monte Carlo simulations. Also, comparisons with the most known tests in the literature are placed to validate the usefulness of the proposed results. Finally, we achieve significantly more powerful tests as compared to the classical ones with comparable error rates.

Suggested Citation

  • Thomas Gkelsinis & Alex Karagrigoriou & Vlad Stefan Barbu, 2022. "Statistical inference based on weighted divergence measures with simulations and applications," Statistical Papers, Springer, vol. 63(5), pages 1511-1536, October.
    • Handle: RePEc:spr:stpapr:v:63:y:2022:i:5:d:10.1007_s00362-022-01286-z
    DOI: 10.1007/s00362-022-01286-z
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    References listed on IDEAS

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    2. Joseph E. Cavanaugh, 2004. "Criteria for Linear Model Selection Based on Kullback's Symmetric Divergence," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 46(2), pages 257-274, June.
    3. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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