“…The statistical tools provided by the BCT framework have been found to provide efficient methods for very effective inference in a variety of applications [21,33,24,30,34]. In terms of the underlying theory, the Bayesian perspective adopted in [21] and this work is neither purely subjective, interpreting the prior and posterior as subjective descriptions of uncertainty pre-and post-data, respectively, nor purely objective, treating the resulting methods as simple black-box procedures [9]. For example, we think of the MAP model as the most accurate, data-driven representation of the regularities present in a given time series, but we inform our analysis of the resulting inferential procedures by simulation experiments on hypothetical models, and by examining their frequentist properties; see, e.g., [3,Chapter 6] or [13,Chapter 4] for broad discussions of the relationship between the Bayesian and classical outlook.…”