A Bayesian Approach to Robust Skewed Autoregressive Processes. Issue 2 (November 2017) - Maleki, Mohsen; Arellano-Valle, Reinaldo B.; Dey, Dipak K.; Mahmoudi, Mohammad R.; Jalali, Seyed Mohammad J.
Abstract: This article studies autoregressive (AR) models assuming innovations with scale mixtures of skew-normal (SMSN) distributions, an attractive and flexible family of probability distributions. A Bayesian analysis considering informative prior distributions is presented. Comprehensive simulation studies are performed to support the performance of the proposed model and methods. The proposed methods are also applied on a real-time series data which has previously been analysed under Gaussian and Student- t AR models.