Afrika Statistika

  • Afr. Stat.
  • Volume 11, Number 2 (2016), 1061 -1074 .

Robust Bayesian Inference of Generalized Pareto Distribution

Fatiha MOKRANI, Hocine FELLAG, and Abdelhakim NECIR

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Abstract

In this work, robust Bayesian estimation of the generalized Pareto distribution is proposed. The methodology is presented in terms of oscillation of posterior risks of the Bayesian estimators. By using a Monte Carlo simulation study, we show that, under a suitable generalized loss function, we can obtain a robust Bayesian estimator of the model.

Résumé

Dans ce travail, nous présentons une analyse de robustesse Bayesienne des estimateurs des paramétres dun modèle de Pareto généralisé en termes d'oscillation des risques a posteriori. En utilisant une étude exhaustive de Monte Carlo, nous prouvons que, moyennant une fonsction perte généralisée adéquate, on peut construire un estimateur Bayesien robuste du modèle.

Article information

Source
Afr. Stat., Volume 11, Number 2 (2016), 1061 -1074 .

Dates
First available in Project Euclid: 20 January 2017

Permanent link to this document
https://projecteuclid.org/euclid.as/1484881315

Digital Object Identifier
doi:10.16929/as/2016.1061.92

Mathematical Reviews number (MathSciNet)
MR3599807

Zentralblatt MATH identifier
1358.62032

Subjects
Primary: 62F15: Bayesian inference 62F35: Robustness and adaptive procedures

Keywords
Bayesian estimation Extreme value Generalized Fisher information Generalized Pareto distribution Monte Carlo Robustness

Citation

MOKRANI, Fatiha; FELLAG, Hocine; NECIR, Abdelhakim. Robust Bayesian Inference of Generalized Pareto Distribution. Afr. Stat. 11 (2016), no. 2, 1061 --1074. doi:10.16929/as/2016.1061.92. https://projecteuclid.org/euclid.as/1484881315


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