Bayesian mixture autoregressive model with Student's t innovations

2021/09/02 by Davide Ravagli, Ravagli, Davide, Georgi N. Boshnakov +1
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #G3 #Methodology (stat.ME) #Statistical Distribution Estimation and Applications #Statistical Methods and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.2109.01083

openalex publication_date 2021/09/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper introduces a fully Bayesian analysis of mixture autoregressive models with Student t components. With the capacity of capturing the behaviour in the tails of the distribution, the Student t MAR model provides a more flexible modelling framework than its Gaussian counterpart, leading to fitted models with fewer parameters and of easier interpretation. The degrees of freedom are also treated as random variables, and hence are included in the estimation process.

Related

• A mixture autoregressive model based on Student's t-distribution
• A mixture autoregressive model based on Gaussian and Student's t-distributions
• Bayesian analysis of mixture autoregressive models covering the complete parameter space
• Hidden Markov Mixture Autoregressive Models: Parameter Estimation
• Gaussian and Student's t mixture vector autoregressive model with application to the effects of the Euro area monetary policy shock