Robust bayesian analysis of an autoregressive model with exponential innovations

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.

Keywords: Autoregressive process; Bayes; Estimation; Exponential; Loss function; Robustness