| Learning to signal: Analysis of a micro-level reinforcement model R Argiento, R Pemantle, B Skyrms, S Volkov Stochastic processes and their applications 119 (2), 373-390, 2009 | 124 | 2009 |
| An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data WD Wadsworth, R Argiento, M Guindani, J Galloway-Pena, SA Shelburne, ... BMC bioinformatics 18, 1-12, 2017 | 94 | 2017 |
| Bayesian density estimation and model selection using nonparametric hierarchical mixtures R Argiento, A Guglielmi, A Pievatolo Computational Statistics & Data Analysis 54 (4), 816-832, 2010 | 52 | 2010 |
| Is infinity that far? A Bayesian nonparametric perspective of finite mixture models R Argiento, M De Iorio The Annals of Statistics 50 (5), 2641-2663, 2022 | 44 | 2022 |
| Distributed interruptible load shedding and micro-generator dispatching to benefit system operations R Argiento, R Faranda, A Pievatolo, E Tironi IEEE Transactions on Power Systems 27 (2), 840-848, 2011 | 41 | 2011 |
| Bayesian analysis and prediction of failures in underground trains A Pievatolo, F Ruggeri, R Argiento Quality and Reliability Engineering International 19 (4), 327-336, 2003 | 33 | 2003 |
| Hierarchical normalized completely random measures to cluster grouped data R Argiento, A Cremaschi, M Vannucci Journal of the American Statistical Association, 2020 | 29 | 2020 |
| A blocked Gibbs sampler for NGG-mixture models via a priori truncation R Argiento, I Bianchini, A Guglielmi Statistics and Computing 26 (3), 641-661, 2016 | 27 | 2016 |
| A “density-based” algorithm for cluster analysis using species sampling Gaussian mixture models R Argiento, A Cremaschi, A Guglielmi Journal of Computational and Graphical Statistics 23 (4), 1126-1142, 2014 | 26 | 2014 |
| Posterior sampling from -approximation of normalized completely random measure mixtures R Argiento, I Bianchini, A Guglielmi | 25 | 2016 |
| A Bayesian framework for describing and predicting the stochastic demand of home care patients R Argiento, A Guglielmi, E Lanzarone, I Nawajah Flexible Services and Manufacturing Journal 28, 254-279, 2016 | 20 | 2016 |
| MCMC computations for Bayesian mixture models using repulsive point processes M Beraha, R Argiento, J Møller, A Guglielmi Journal of Computational and Graphical Statistics 31 (2), 422-435, 2022 | 19 | 2022 |
| Bias correction in clustered underreported data G Lopes de Oliveira, R Argiento, R Helena Loschi, R Martins Assunção, ... Bayesian Analysis 17 (1), 95-126, 2022 | 17 | 2022 |
| A comparison of nonparametric priors in hierarchical mixture modelling for AFT regression R Argiento, A Guglielmi, A Pievatolo Journal of Statistical Planning and Inference 139 (12), 3989-4005, 2009 | 15 | 2009 |
| Hierarchical normalized completely random measures for robust graphical modeling A Cremaschi, R Argiento, K Shoemaker, C Peterson, M Vannucci Bayesian analysis 14 (4), 1271, 2019 | 12 | 2019 |
| Modeling the association between clusters of SNPs and disease responses R Argiento, A Guglielmi, CK Hsiao, F Ruggeri, C Wang Nonparametric Bayesian Inference in Biostatistics, 115-134, 2015 | 12 | 2015 |
| Gaussian graphical modeling for spectrometric data analysis L Codazzi, A Colombi, M Gianella, R Argiento, L Paci, A Pini Computational statistics & data analysis 174, 107416, 2022 | 11 | 2022 |
| Bayesian joint modelling of the health profile and demand of home care patients R Argiento, A Guglielmi, E Lanzarone, I Nawajah IMA Journal of Management Mathematics 28 (4), 531-552, 2017 | 11 | 2017 |
| Efficient uncertainty quantification in stochastic finite element analysis based on functional principal components I Bianchini, R Argiento, F Auricchio, E Lanzarone Computational Mechanics 56, 533-549, 2015 | 9 | 2015 |
| Multilevel functional principal component analysis of facade sound insulation data R Argiento, PG Bissiri, A Pievatolo, C Scrosati Quality and Reliability Engineering International 31 (7), 1239-1253, 2015 | 7 | 2015 |
