2 papers
stat.ME2026
Marginal Data Augmentation for Efficient Bayesian Modeling of Counts and Rates with a Demographic Application
Gregor Zens, Sylvia Frühwirth-Schnatter
Count data models are ubiquitous in many fields, yet Bayesian data augmentation algorithms for such models frequently encounter challenges with Markov chain Monte Carlo efficiency.…
stat.ME2024
Without Pain -- Clustering Categorical Data Using a Bayesian Mixture of Finite Mixtures of Latent Class Analysis Models
Gertraud Malsiner-Walli, Bettina Grün, Sylvia Frühwirth-Schnatter
We propose a Bayesian approach for model-based clustering of multivariate categorical data where variables are allowed to be associated within clusters and the number of clusters i…