Afrika Statistika

Robust bayesian analysis of an autoregressive model with exponential innovations

Lydia LARBI and Hocine FELLAG

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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.


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

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

First available in Project Euclid: 12 July 2016

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Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

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

Autoregressive process Bayes Estimation Exponential Loss function Robustness


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.

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