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The extended exponential power distribution and Bayesian robustness

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  • Choy, S. T. Boris
  • Walker, Stephen G.

Abstract

In this paper, it is demonstrated that an extension to the exponential power family allows for robustness characteristics for the normal location parameter problem, previously thought to be restricted to the Student-t and a subclass of the positive stable families.

Suggested Citation

  • Choy, S. T. Boris & Walker, Stephen G., 2003. "The extended exponential power distribution and Bayesian robustness," Statistics & Probability Letters, Elsevier, vol. 65(3), pages 227-232, November.
    • Handle: RePEc:eee:stapro:v:65:y:2003:i:3:p:227-232
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    References listed on IDEAS

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    1. S. T. Boris Choy & Adrian F. M. Smith, 1997. "On Robust Analysis of a Normal Location Parameter," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(2), pages 463-474.
    2. S. Choy & A. Smith, 1997. "Hierarchical models with scale mixtures of normal distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 6(1), pages 205-221, June.
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    Citations

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    Cited by:

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    3. Wan, Wai-Yin & Chan, Jennifer So-Kuen, 2011. "Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 687-702, January.
    4. Fung, Thomas & Seneta, Eugene, 2008. "A characterisation of scale mixtures of the uniform distribution," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2883-2888, December.
    5. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2021. "Posterior moments and quantiles for the normal location model with Laplace prior," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(17), pages 4039-4049, August.
    6. Saralees Nadarajah, 2006. "Acknowledgement of Priority: the Generalized Normal Distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(9), pages 1031-1032.
    7. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
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    9. Bernardi, Mauro & Bottone, Marco & Petrella, Lea, 2018. "Bayesian quantile regression using the skew exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 92-111.

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