We develop Bayesian methods of analysis for a new class of Threshold Autoregressive models: Endogenous Delay Threshold. We apply our methods to the commonly used sunspot data data set and find strong evidence in favor of the EDTAR model over linear and tranditional threshold autoregressions.

In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, 'diffuse' priors on model-specific parameters can lead to quite unexpected...