The effect of observations on Bayesian choice of an autoregressive model

We consider the effect, on a Bayes factor, of omitting observations in time-series models. In particular, we study a Bayes factor for deciding between autoregressive models of different orders. Throughout we use Gibbs sampling to estimate the parameters of the models and the marginal densities. We illustrate the methods using data generated from an autoregressive model and some data on bag snatching in the Hyde Park area of Chicago. Copyright 2006 Blackwell Publishing Ltd.