Bayesian analysis of mixture autoregressive models covering the complete parameter space

@article{Ravagli2021BayesianAO,
  title={Bayesian analysis of mixture autoregressive models covering the complete parameter space},
  author={Davide Ravagli and Georgi N. Boshnakov},
  journal={Computational Statistics},
  year={2021}
}
Mixture autoregressive (MAR) models provide a flexible way to model time series with predictive distributions which depend on the recent history of the process and are able to accommodate asymmetry and multimodality. Bayesian inference for such models offers the additional advantage of incorporating the uncertainty in the estimated models into the predictions. We introduce a new way of sampling from the posterior distribution of the parameters of MAR models which allows for covering the… 
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