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Professore Ordinario
Dipartimento di Scienze delle Decisioni

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Insegnamenti a.a. 2018/2019


Insegnamenti a.a. precedenti

Note biografiche

Laurea con lode in Discipline Economiche e Sociali presso l'Università Bocconi. Dottorato di ricerca in Statistica metodologica, Università di Trento (1989).

Curriculum Accademico

Sonia Petrone e' Professore Ordinario di Statistica presso l'Università Bocconi, e Direttrice del PhD in Statistics Bocconi. Ha insegnato precedentemente presso l'Università di Pavia e l'Università dell'Insubria. Ha svolto periodi di ricerca presso diverse università e istituti di ricerca esteri, fra cui Stanford University, University of Cornell, University of Washington, Duke University, Institute for Mathematics and its Applications - University of Minnesota, Indian Statistical Institute, Russian Academy of Science, Universidad Catòlica de Chile.

Servizio professionale e editoriale: President Elect (2013), President (2014) e Past President (2015) della International Society for Bayesian Analysis (ISBA) . Membro del Council dell''Institute of Mathematical Statistics (IMS) (2011-2014). Membro del Board of Directors ISBA (2002-2004 e 2008-2010). Membro (2012)  e Chair (2013 e 2014) dell'IMS Committee on Travel Awards. ISBA: Constitution and Bylaws Committee (2012-2017);  Chair (2012) e membro (2010) del Savage Award Committee; Chair (2015) e membro(2009) del de Groot Prize Committee; 

Project evaluator and referee: National Science Foundation (USA); Netherlands Organization for Scientific Research (NWO); Conicyt (Chile); Milano Univ.; Padova Univ.

Co-editor di Bayesian Analysis (2010-2014). Associate Editor di Statistical Science.

Ha fatto parte del comitato scientifico e organizzatore di numerosi convegni scientifici internazionali, fra cui la serie di workshop su "Bayesian nonparametrics" e "Bayesian Inference for Stochastic Processes" (BISP). 

Ha ottenuto i riconoscimenti "eccellenza nella ricerca" dell'Università Bocconi (2002, 2003; 2009-2010; 2011-2012; 2013-2014; 2015-2016).


Aree di interesse scientifico

Statistica Bayesiana: fondamenti, metodi, applicazioni.  Metodi bayesiani nonparametrici. Modelli  a variabili latenti.  Metodi e modelli previsivi. Modelli per sistemi dinamici e state space models.  

Pubblicazioni principali

Fortini, S. and Petrone, S. (2015). Predictive Characterization of Mixtures of Markov Chains. Bernoulli, to  appear.
Fortini, S. and Petrone, S. (2015). Predictive distribution: de Finetti’s view. Wiley StatsRef-Statistics Reference Online.
Petrone, S., Rousseau, J. and Scricciolo, C. (2014). Bayes and Empirical Bayes: do they merge?. Biometrika, 101, 285–302.
Wade, S.K., Dunson, D.B., Petrone, S. and Trippa, L. (2014). Improving Prediction from Dirichlet Process Mixtures via Enrichment. Journal of Machine Learning Research, 15, 1041–1071.
Petrone, S., Rizzelli, S., Rousseau, J., Scricciolo, C. (2014). Empirical Bayes methods in classical and Bayesian inference. METRON, 72, 201–215.
Wade, S., Walker, S. and Petrone, S. (2014). A Predictive Study of Dirichlet Process Mixture Models for Curve Fitting. Scandinavian Journal of Statistics, 41, 580–605.
Fortini, S. and Petrone, S. (2012). Hierarchical Reinforced Urn Processes. Statistics and Probability Letters, 82, 1521-1529.
Fortini, S. and Petrone, S. (2012). Predictive construction of priors in Bayesian nonparametrics. Brazilian Journal of Probability and Statistics, 26, 423-449.   
Petris, G. and Petrone, S. (2011) State space models in R. Journal of Statistical Software.  
Wade, S., Mongelluzzo, S. and Petrone, S. (2010). Enriched conjugate priors for Bayesian nonparametric inference. Bayesian Analysis, 6, 359-386.     
Petrone, S., Guindani, M. and Gelfand, A.E. (2009) "Hybrid Dirichlet mixture models for functional data", Journal Royal Statistical Society, Ser. B, 71, 755-782.  
Petris, G., Petrone, S. and Campagnoli, P. (2009) Dynamic linear models with R, Springer, N.Y..    Trippa, L., Bulla, P. and Petrone, S. (2011) "Extended Bernstein prior via reinforced urn processes", Annals of the Institute of Statistical Mathematics,63, 481-469 (online 2009).    Petrone, S. and Veronese, P.  "Feller operators and mixture priors in Bayesian nonparametrics" (Statistica Sinica, 2010, 20, 379-404 ).     N.L.Hjort and Petrone, S. (2007) "Nonparametric quantile inference with Dirichlet processes", in: Advances in Statistical Modeling and Inference. Essays in Honor of Kjell A Doksum,  V. Nair Ed., 463-492.    A.E. Gelfand, M. Guindani and Petrone, S. (2007) "Bayesian nonparametric modelling for spatial data using Dirichlet processes" (with discussion), in: Bayesian Statistics 8, J.M. Bernardo, J.O. Berger, Dawid, A.P. and A.F.M. Smith Eds, Oxford University Press. Petrone, S. (2007) Discussion on "Approximating interval hypothesis: p-values and Bayes factors", by J. Russeau; in:  Bayesian Statistics 8, J.M. Bernardo, J.O.Berger, Dawid, A.P. and A.F.M. Smith Eds., Oxford University Press. Petrone, S. (2003) "A predictive point of view  on Bayesian nonparametrics"; in: Highly Structured Stochastic Systems, P. Green, N. Hjort and S. Richardson Eds, Oxford University Press. Petrone, S. and Wasserman, L. (2002) Consistency of Bernstein Polynomial Density Estimators, Journal of the Royal Statistical Society, Ser. B, 64, 79-100; Petrone, S. and Veronese, P. (2002) Non Parametric Mixture Priors Based on an Exponential Random Scheme, Statistical Methods and Applications, 11, 1-20. Campagnoli, P., Muliere,P. and Petrone, S. (2001) Generalized Dynamic Linear Models for Financial Time Series, Applied Stochastic Models in Business and Industry, 17, 27-39; Petrone, S. and Corielli, F. (2005) Dynamic Regression Using Bernstein Polynomials with Application to Estimation of the Term Structure of Interest Rates Studi Statistici 61, IMQ, Università Bocconi;  Petrone, S. (1999) Random Bernstein Polynomials, Scandinavian Journal of Statistics , 26, 373-393; Petrone, S. (1999)  Bayesian Density Estimation Using Bernstein Polynomials, Canadian Journal of Statistics, 27, 105-126; Petrone, S. (1999) Discussion on "Bayesian nonparametric inference for random distributions and related functions", by Walker, S.G., Damien, P., Laud, P.W., Smith, A.F.M., Journal of the Royal  Statistics Society, Ser. B, 61, 522-523. Petrone, S., Roberts, G.O. and Rosenthal, J.S. (1999) A Note on Convergence Rates of Gibbs Sampling for Nonparametric Mixtures, Far East Journal of Theoretical Statistics, 3, 213-225; Petrone, S. and Raftery, A.E. (1997) A Note on the Dirichlet Process Prior in Bayesian Nonparametric Inference with Partial Exchangeability, Statistics and Probability Letters, 36, 69-83. Mira, A. and Petrone, S. (1996) Bayesian Hierarchical Nonparametric Inference for Change-point Problems; in: J.M. Bernardo, J.O. Berger, A.P. Dawid, A.F.M. Smith (eds.), Bayesian Statistics 5, Oxford University Press, 693-703. Muliere, P. and Petrone, S. (1993) A Bayesian predictive approach to sequential searching for  an optimal dose: parametric and nonparametric models, Journal of the  Italian Statistical Society, 3, 349-364. Muliere, P. and Petrone, S. (1992) Generalized Lorenz curve and monotone  dependence orderings, Metron, L, 19-38.