Afrika Statistika

Robust bayesian analysis of an autoregressive model with exponential innovations

Lydia LARBI and Hocine FELLAG

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Abstract

In this work, robust Bayesian analysis of the Bayesian estimation of an autoregressive model with exponential innovations is performed. Using a Bayesian robustness methodology, we show that, using a suitable generalized quadratic loss, we obtain optimal Bayesian estimators of the parameters corresponding to the smallest oscillation of the posterior risks.

Résumé

Dans ce travail, nous considérons l'estimation Bayésienne du paramétre d'un processus auto-régressif d'ordre un avec erreurs exponentielles. En utilisant une méthodologie de robustesse Bayésienne appropriée et une fonction perte quadratique généralisée adéquate, nous montrons qu'on peut construire un estimateur Bayésien robuste correspondant à la plus petite oscillation du risque à posteriori.

Article information

Source
Afr. Stat., Volume 11, Number 1 (2016), 955-964.

Dates
First available in Project Euclid: 12 July 2016

Permanent link to this document
https://projecteuclid.org/euclid.as/1468344420

Digital Object Identifier
doi:10.16929/as/2016.955.86

Mathematical Reviews number (MathSciNet)
MR3522311

Zentralblatt MATH identifier
1342.62150

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

Keywords
Autoregressive process Bayes Estimation Exponential Loss function Robustness

Citation

LARBI, Lydia; FELLAG, Hocine. Robust bayesian analysis of an autoregressive model with exponential innovations. Afr. Stat. 11 (2016), no. 1, 955--964. doi:10.16929/as/2016.955.86. https://projecteuclid.org/euclid.as/1468344420


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