3 papers
math.ST2025
Bayesian Mixtures Models with Repulsive and Attractive Atoms
Mario Beraha, Raffaele Argiento, Federico Camerlenghi +1
The study of almost surely discrete random probability measures is an active line of research in Bayesian nonparametrics. The idea of assuming interaction across the atoms of the r…
stat.ME2024
Nested Compound Random Measures
Federico Camerlenghi, Riccardo Corradin, Andrea Ongaro
Nested nonparametric processes are vectors of random probability measures widely used in the Bayesian literature to model the dependence across distinct, though related, groups of…
stat.ME2024
Hierarchical Mixture of Finite Mixtures
Alessandro Colombi, Raffaele Argiento, Federico Camerlenghi +1
Statistical modelling in the presence of data organized in groups is a crucial task in Bayesian statistics. The present paper conceives a mixture model based on a novel family of B…