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B0582
Title: Hierarchical and time-dependent random partitions based on the shrinkage partition distribution Authors:  David Dahl - Brigham Young University (United States) [presenting]
Richard Warr - Brigham Young University (United States)
Thomas Jensen - Brigham Young University (United States)
Abstract: Bayesian nonparametric models often rely on clustering models that borrow strength within and between groups. In a scenario where researchers have some notion of the clustering composition, we propose the shrinkage partition distribution, which allows for tractable posterior analysis based on the researchers' prior knowledge. The shrinkage partition distribution (SPD) shrinks any baseline random partition distribution towards a baseline partition. An extension to any sequentially-allocated partition model, SPD is extremely flexible with relatively inexpensive posterior simulation. We show several distinct advantages over the existing methods, including the ability to model dependent random partitions. Specifically, we show that the SPD can hierarchically model a collection of random partition distributions and can also model time-dependent random partitions.