2 citations · 3 across the 9 of their papers we have counts for
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BayesChange: an R package for Bayesian Change Point Analysis
Luca Danese, Riccardo Corradin, Andrea Ongaro
We introduce BayesChange, a computationally efficient R package, built on C++, for Bayesian change point detection and clustering of observations sharing common change points. Whil…
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…
Importance conditional sampling for Pitman-Yor mixtures
Antonio Canale, Riccardo Corradin, Bernardo Nipoti
Nonparametric mixture models based on the Pitman-Yor process represent a flexible tool for density estimation and clustering. Natural generalization of the popular class of Dirichl…