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Bayesian nonparametric model based clustering with intractable distributions: an ABC approach
Mario Beraha, Riccardo Corradin
Bayesian nonparametric mixture models offer a rich framework for model based clustering. We consider the situation where the kernel of the mixture is available only up to an intrac…
Contaminated Gibbs-type priors
Federico Camerlenghi, Riccardo Corradin, Andrea Ongaro
Gibbs-type priors are widely used as key components in several Bayesian nonparametric models. By virtue of their flexibility and mathematical tractability, they turn out to be pred…
Optimal stratification of survival data via Bayesian nonparametric mixtures
Riccardo Corradin, Luis Enrique Nieto-Barajas, Bernardo Nipoti
The stratified proportional hazards model represents a simple solution to account for heterogeneity within the data while keeping the multiplicative effect on the hazard function.…