6 papers
Similarity-Driven Proposals for MCMC Algorithms on Discrete Spaces
Luca Aiello, Raffaele Argiento, Alexandros Beskos +1
Recent research has led to the development of MCMC algorithms with likelihood-informed proposals when targeting posterior distributions supported on discrete state spaces. Our work…
Bayesian discovery of species in multiple areas
Alessandro Colombi, Raffaele Argiento, Federico Camerlenghi +1
In ecology, the description of species composition and biodiversity calls for statistical methods that involve estimating features of interest in unobserved samples based on an obs…
Modeling Spatio-Temporal Dynamics of Obesity in Italian Regions Via Bayesian Beta Regression
Luciano Rota, Raffaele Argiento, Michela Cameletti
In this paper we investigate the spatio-temporal dynamics of obesity rates across Italian regions from 2010 to 2022, aiming to identify spatial and temporal trends and assess poten…
Addressing Phase Discrepancies in Functional Data: A Bayesian Approach for Accurate Alignment and Smoothing
Jacopo Gardella, Raffaele Argiento, Alessandro Casa +1
In many real-world applications, functional data exhibit considerable variability in both amplitude and phase. This is especially true in biomechanical data such as the knee flexio…
Bayesian nonparametric clustering for spatio-temporal data, with an application to air pollution
Luca Aiello, Raffaele Argiento, Sirio Legramanti +1
Air pollution is a major global health hazard, with fine particulate matter (PM10) linked to severe respiratory and cardiovascular diseases. Hence, analyzing and clustering spatio-…
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…