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
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]
