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20152022
most citedA priori truncation method for posterior sampling from homogeneous normalized completely random measure mixture models

2 citations · 5 across the 5 of their papers we have counts for

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5 papers · 1 filter

stat.ME20221 cited

Clustering blood donors via mixtures of product partition models with covariates

Raffaele Argiento, Riccardo Corradin, Alessandra Guglielmi +1

Motivated by the problem of accurately predicting gap times between successive blood donations, we present here a general class of Bayesian nonparametric models for clustering. The…

stat.ME2021

Gaussian graphical modeling for spectrometric data analysis

Laura Codazzi, Alessandro Colombi, Matteo Gianella +3

Motivated by the analysis of spectrometric data, we introduce a Gaussian graphical model for learning the dependence structure among frequency bands of the infrared absorbance spec…

stat.ME2021

Bayesian GARCH Modeling of Functional Sports Data

Patric Dolmeta, Raffaele Argiento, Silvia Montagna

The use of statistical methods in sport analytics has gained a rapidly growing interest over the last decade, and nowadays is common practice. In particular, the interest in unders…

stat.ME2020

MCMC computations for Bayesian mixture models using repulsive point processes

Mario Beraha, Raffaele Argiento, Jesper Møller +1

Repulsive mixture models have recently gained popularity for Bayesian cluster detection. Compared to more traditional mixture models, repulsive mixture models produce a smaller num…

stat.ME20192 cited

Is infinity that far? A Bayesian nonparametric perspective of finite mixture models

Raffaele Argiento, Maria De Iorio

Mixture models are one of the most widely used statistical tools when dealing with data from heterogeneous populations. This paper considers the long-standing debate over finite mi…