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Title: Random partition distribution concentrated around a focal partition Authors:  David Dahl - Brigham Young University (United States) [presenting]
Richard Warr - Brigham Young University (United States)
Thomas Jensen - Brigham Young University (United States)
Abstract: Random partition models, such as the Chinese restaurant process, allow a Bayesian model to flexibly borrow strength. While many partition priors are exchangeable, we propose a nonexchangeable prior based on a focal partition, a Bayesian's prior guess for the unknown partition. We show how our approach modifies the Chinese restaurant process so that partitions that are similar to the focal partition have higher probability. There is a weight parameter that varies between 0 and infinity, where 0 corresponds to the original Chinese restaurant process and infinity yields a point mass distribution at the focal partition. In motivation and spirit, our approach is similar to another recent one. In contrast, however, we have a tractable normalizing constant so inference can easily be made on the weight and mass parameter. We investigate the similarity and difference between these approaches.