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stat.ME2023
Informed Random Partition Models with Temporal Dependence
Sally Paganin, Garritt L. Page, Fernando Andrés Quintana
Model-based clustering is a powerful tool that is often used to discover hidden structure in data by grouping observational units that exhibit similar response values. Recently, cl…
stat.ME2023
Computational methods for fast Bayesian model assessment via calibrated posterior p-values
Sally Paganin, Perry de Valpine
Posterior predictive p-values (ppps) have become popular tools for Bayesian model assessment, being general-purpose and easy to use. However, interpretation can be difficult becaus…
stat.ME2019
Centered Partition Process: Informative Priors for Clustering
Sally Paganin, Amy H. Herring, Andrew F. Olshan +1
There is a very rich literature proposing Bayesian approaches for clustering starting with a prior probability distribution on partitions. Most approaches assume exchangeability, l…