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Use of exponential power distributions for mixture models in the presence of covariates

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  • Jorge Alberto Achcar
  • Gilberto De AraUJo Pereira

Abstract

In this paper, we present a Bayesian analysis of exponential power mixture models in the presence of a covariate. Considering Gibbs sampling with MetropolisHastings algorithms, we obtain Monte Carlo estimates for the posterior quantities of interest.

Suggested Citation

  • Jorge Alberto Achcar & Gilberto De AraUJo Pereira, 1999. "Use of exponential power distributions for mixture models in the presence of covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 669-679.
  • Handle: RePEc:taf:japsta:v:26:y:1999:i:6:p:669-679
    DOI: 10.1080/02664769922115
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    Cited by:

    1. Hazan, Alon & Landsman, Zinoviy & E Makov, Udi, 2003. "Robustness via a mixture of exponential power distributions," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 111-121, February.
    2. Wang, Min & Lu, Tao, 2015. "A matching prior for the shape parameter of the exponential power distribution," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 150-154.
    3. Mineo, Angelo & Ruggieri, Mariantonietta, 2005. "A Software Tool for the Exponential Power Distribution: The normalp Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i04).
    4. repec:jss:jstsof:12:i04 is not listed on IDEAS

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