activity
20152026
most citedCentered Partition Process: Informative Priors for Clustering

17 citations · 24 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ME2026

Dynamic Extended Generalized Many-Facet Rasch Model: A Unified Approach to Rater-Mediated Assessment

Giuseppe Mignemi, Patrícia Martinková, Sally Paganin

Rating procedures are crucial in psychological and medical diagnosis, educational assessment, peer review, and grant evaluation. A major methodological challenge is disentangling m…

stat.ME2023★ 1 cited

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.ME2021

Computational strategies and estimation performance with Bayesian semiparametric Item Response Theory models

Sally Paganin, Christopher J. Paciorek, Claudia Wehrhahn +3

Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions bas…

stat.ME2019★ 17 cited

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…

stat.AP2015★ 6 cited

Bayesian modeling of networks in complex business intelligence problems

Daniele Durante, Sally Paganin, Bruno Scarpa +1

Complex network data problems are increasingly common in many fields of application. Our motivation is drawn from strategic marketing studies monitoring customer choices of specifi…