This paper offers an approach to time series modeling that attempts to reconcile classical and Bayesian methods. The central idea put forward to achieve this reconciliation is that the Bayesian approach relies implicitly on a frame of reference for the data generating mechanism that is quite...

If data exhibit a dimensional structure more complex than what is assumed, key conditional independence assumptions of the hypothesized model do not hold. The current work pursues posterior predictive model checking, a flexible family of Bayesian model checking procedures, as a tool for...