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Gabriele Soffritti

Professore ordinario

Dipartimento di Scienze Statistiche "Paolo Fortunati"

Settore scientifico disciplinare: SECS-S/01 STATISTICA

Coordinatore del Corso di Laurea Magistrale in Statistical Sciences

Pubblicazioni

Galimberti, Giuliano; Manisi, Annamaria; Soffritti, Gabriele, Modelling the role of variables in model-based cluster analysis, «STATISTICS AND COMPUTING», 2018, 28, pp. 145 - 169 [articolo]Open Access

Saverio Ranciati, Giuliano Galimberti, Gabriele Soffritti, Bayesian variable selection in linear regression models with non-normal errors, in: F. Greselin, F. Mola, M. Zenga, Cladag 2017. Book of short papers, Mantova, Universitas Studiorum srl, 2017, pp. 1 - 6 (atti di: International Conference of The CLAssification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), Milan, Italy, September 13-15, 2017) [Contributo in Atti di convegno]

Galimberti, Giuliano; Scardovi, Elena; Soffritti, Gabriele, Using mixtures in seemingly unrelated linear regression models with non-normal errors, «STATISTICS AND COMPUTING», 2016, 26, pp. 1025 - 1038 [articolo]

Giuliano Galimberti; Gabriele Soffritti, A multivariate linear regression analysis using finite mixtures of t distributions, «COMPUTATIONAL STATISTICS & DATA ANALYSIS», 2014, 71, pp. 138 - 150 [articolo]

Merni F.; Di Michele R.; Soffritti G., Assessment of handedness using latent class factor analysis, «LATERALITY», 2014, 19, pp. 405 - 423 [articolo]

Galimberti G.; Soffritti G., Using conditional independence for parsimonious model-based Gaussian clustering, «STATISTICS AND COMPUTING», 2013, 23, pp. 625 - 638 [articolo]

Galimberti G.; Soffritti G.; Di Maso M., Classification Trees for Ordinal Responses in R: The rpartScore Package, «JOURNAL OF STATISTICAL SOFTWARE», 2012, 47 (Issue 10), pp. 1 - 25 [articolo]

G. Galimberti; G. Soffritti; M. Di Maso, rpartScore: Classification trees for ordinal responses, 2012. [software]

G. Galimberti; G. Soffritti, Tree-based methods and decision trees, in: Modern Analysis of Customer Surveys: with applications using R, CHICHESTER, John Wiley & Sons, 2012, pp. 283 - 307 [capitolo di libro]

G. Soffritti; G. Galimberti, Multivariate linear regression with non-normal errors: a solution based on mixture models, «STATISTICS AND COMPUTING», 2011, 21, pp. 523 - 536 [articolo]

G. Galimberti; M. Pillati; G. Soffritti, Notes on the robustness of regression trees against skewed and contaminated errors, in: New Perspectives in Statistical Modeling and Data Analysis, BERLIN, Springer-Verlag, «STUDIES IN CLASSIFICATION, DATA ANALYSIS, AND KNOWLEDGE ORGANIZATION», 2011, pp. 255 - 263 (atti di: 7th Conference of the Classification and Data Analysis Group of the Italian Statistical Society, Catania, Italy, September 9-11, 2009) [Contributo in Atti di convegno]

Galimberti G.; Soffritti G., Finite mixture models for clustering multilevel data with multiple cluster structures, «STATISTICAL MODELLING», 2010, 10(3), pp. 265 - 290 [articolo]

G. Soffritti; G. Galimberti, Detecting multiple cluster structures through model-based clustering methods, in: Classification and Data Analysis 2009, PADOVA, CLEUP, 2009, pp. 263 - 266 (atti di: 7° Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Catania, Italy, September 9-11 2009) [Contributo in Atti di convegno]

G. Cavrini; G. Galimberti; G. Soffritti, Evaluating patient satisfaction through latent class factor analysis, «HEALTH & PLACE», 2009, 15, pp. 210 - 218 [articolo]

M. Di Martino; G. Galimberti; G. Soffritti, Evaluating public services through multivariate linear regression analysis, «QUADERNI DI STATISTICA», 2009, 11, pp. 183 - 201 [articolo]

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