On the Bayesian Two-Sample Problem for Ranking Data

We consider the two-sample problem involving a new class of angle-based models for ranking data. These models are functions of the cosine of the angle between a ranking and a consensus vector. A Bayesian approach is employed to determine the corresponding predictive densities. Two competing hypotheses are considered, and we compute the Bayes factor to quantify the evidence provided by the observed data under each hypothesis. We apply the results to a real data set.