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Empirical likelihood based inference for conditional Pareto-type tail index

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  • Ma, Yaolan
  • Jiang, Yuexiang
  • Huang, Wei

Abstract

We propose empirical likelihood-based statistics to construct confidence regions for the regression coefficient of the parametric tail index regression model. Our limited simulation study shows the method is more accurate than the normal approximation in terms of coverage probability.

Suggested Citation

  • Ma, Yaolan & Jiang, Yuexiang & Huang, Wei, 2018. "Empirical likelihood based inference for conditional Pareto-type tail index," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 114-121.
    • Handle: RePEc:eee:stapro:v:134:y:2018:i:c:p:114-121
    DOI: 10.1016/j.spl.2017.10.021
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    References listed on IDEAS

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    Cited by:

    1. Hongyu An & Boping Tian, 2024. "Varying Index Coefficient Model for Tail Index Regression," Mathematics, MDPI, vol. 12(13), pages 1-35, June.

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