Corander, Jukka; Villani, Mattias - In: Journal of Time Series Analysis 27 (2006) 1, pp. 141-156
We introduce a Bayesian approach to model assessment in the class of graphical vector autoregressive processes. As a result of the very large number of model structures that may be considered, simulation-based inference, such as Markov chain Monte Carlo, is not feasible. Therefore, we derive an...