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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

Ruolo editoriale nella rivista «Communications in Statistics - Simulation and Computation»

Ruolo editoriale nella rivista «Communications in Statistics - Theory and Methods»

Perrone Gabriele; Soffritti Gabriele, Mixtures of linear regression models: An application to housing tension in Emilia-Romagna, Italy, in: Programme and abstracts, 2023, pp. 16 - 17 (atti di: 25th International Conference on Computational Statistics (COMPSTAT 2023), Birkbeck, University of London, UK, 22-25 August 2023) [atti di convegno-abstract]

Gabriele Perrone; Gabriele Soffritti, Parsimonious mixtures of seemingly unrelated contaminated normal regression models, in: Classification and Data Science in the Digital Age, Cham, Springer, «STUDIES IN CLASSIFICATION, DATA ANALYSIS, AND KNOWLEDGE ORGANIZATION», 2023, pp. 303 - 311 (atti di: 17th Conference of the International Federation of Classification Societies (IFCS 2022), Porto, Portugal, 19-23 July, 2022) [Contributo in Atti di convegno]

Perrone G.; Soffritti G., Seemingly unrelated clusterwise linear regression for contaminated data, «STATISTICAL PAPERS», 2023, 64, pp. 883 - 921 [articolo]Open Access

Cecilia Diani; Giuliano Galimberti; Gabriele Soffritti, Multivariate cluster-weighted models based on seemingly unrelated linear regression, «COMPUTATIONAL STATISTICS & DATA ANALYSIS», 2022, 171, Article number: 107451, pp. 1 - 24 [articolo]

Gabriele Perrone; Gabriele Soffritti, Parsimonious mixtures of seemingly unrelated contaminated normal regression models, in: Book of Abstracts, 2022, pp. 104 - 104 (atti di: 17th Conference of the International Federation of Classification Societies (IFCS2022), Porto, Portugal, 19 - 23 July, 2022) [atti di convegno-abstract]

Gabriele Perrone; Gabriele Soffritti, Parsimonious seemingly unrelated linear cluster-weighted models for contaminated data, in: Program and abstracts, 2022, pp. 52 - 52 (atti di: 24th International Conference on Computational Statistics (COMPSTAT 2022), Bologna, Italy, 23 - 26 August 2022) [atti di convegno-abstract]

Galimberti G.; Nuzzi L.; Soffritti G., Covariance matrix estimation of the maximum likelihood estimator in multivariate clusterwise linear regression, «STATISTICAL METHODS & APPLICATIONS», 2021, 30, pp. 235 - 268 [articolo]Open Access

Soffritti Gabriele, Estimating the Covariance Matrix of the Maximum Likelihood Estimator Under Linear Cluster-Weighted Models, «JOURNAL OF CLASSIFICATION», 2021, 38, pp. 594 - 625 [articolo]Open Access

Galimberti G; Soffritti G, A note on the consistency of the maximum likelihood estimator under multivariate linear cluster-weighted models, «STATISTICS & PROBABILITY LETTERS», 2020, 157, Article number: 108630, pp. 1 - 5 [articolo]Open Access

Gabriele Soffritti, Estimating the covariance matrix of the maximum likelihood estimator under linear cluster-weighted models, in: Program and abstract, 2020, pp. 51 - 51 (atti di: 13th International Conference of the ERCIM Working Group on Computational and Methodological Statistics, Virtual conference, 19 - 21 December 2020) [atti di convegno-abstract]

Giuliano Galimberti; Gabriele Soffritti, Seemingly unrelated clusterwise linear regression, «ADVANCES IN DATA ANALYSIS AND CLASSIFICATION», 2020, 14, pp. 235 - 260 [articolo]

Ranciati, Saverio; Galimberti, Giuliano; Soffritti, Gabriele, Bayesian variable selection in linear regression models with non-normal errors, «STATISTICAL METHODS & APPLICATIONS», 2019, 28, pp. 323 - 358 [articolo]Open Access

Sacco, Chiara; Di Michele, Rocco; Semprini, Gabriele; Merni, Franco; Soffritti, Gabriele*, Joint assessment of handedness and footedness through latent class factor analysis, «LATERALITY», 2018, 23, pp. 643 - 663 [articolo]

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