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Salvatore Ingrassia
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2020 – today
- 2024
- [j32]Luis Angel García-Escudero, Salvatore Ingrassia, Thomas Brendan Murphy:
Special issue on "advances in models and learning for clustering and classification". Adv. Data Anal. Classif. 18(1): 1-4 (2024) - 2023
- [j31]Roberto Di Mari, Salvatore Ingrassia, Antonio Punzo:
Local and Overall Deviance R-Squared Measures for Mixtures of Generalized Linear Models. J. Classif. 40(2): 233-266 (2023) - 2022
- [j30]Salvatore Ingrassia, Julien Jacques, Weixin Yao:
Editorial for ADAC issue 1 of volume 16 (2022). Adv. Data Anal. Classif. 16(1): 1-3 (2022) - [j29]Salvatore Ingrassia, Julien Jacques, Weixin Yao:
Special issue on "Models and learning for clustering and Classification". Adv. Data Anal. Classif. 16(2): 231-234 (2022) - 2021
- [c4]Cinzia Di Nuzzo, Salvatore Ingrassia:
A Graphical Approach for the Selection of the Number of Clusters in the Spectral Clustering Algorithm. SIS 2021: 31-44 - 2020
- [j28]Christophe Biernacki, Luis Angel García-Escudero, Salvatore Ingrassia:
Special issue on "Innovations on model based clustering and classification". Adv. Data Anal. Classif. 14(2): 231-234 (2020) - [j27]Salvatore Ingrassia, Antonio Punzo:
Cluster Validation for Mixtures of Regressions via the Total Sum of Squares Decomposition. J. Classif. 37(2): 526-547 (2020) - [j26]Shuchismita Sarkar, Xuwen Zhu, Volodymyr Melnykov, Salvatore Ingrassia:
On parsimonious models for modeling matrix data. Comput. Stat. Data Anal. 142 (2020)
2010 – 2019
- 2019
- [j25]Sylvia Frühwirth-Schnatter, Salvatore Ingrassia, Agustín Mayo-Íscar:
Special issue on "Advances on model-based clustering and classification" - Preface by the Guest Editors. Adv. Data Anal. Classif. 13(1): 1-5 (2019) - [j24]Jochen Einbeck, John Hinde, Salvatore Ingrassia, Tsung-I Lin, Paul D. McNicholas:
Editorial for the 4th Special Issue on advances in mixture models. Comput. Stat. Data Anal. 132: 143-144 (2019) - 2018
- [j23]Luis Angel García-Escudero, Alfonso Gordaliza, Francesca Greselin, Salvatore Ingrassia, Agustín Mayo-Íscar:
Eigenvalues and constraints in mixture modeling: geometric and computational issues. Adv. Data Anal. Classif. 12(2): 203-233 (2018) - 2017
- [j22]Utkarsh J. Dang, Antonio Punzo, Paul D. McNicholas, Salvatore Ingrassia, Ryan P. Browne:
Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models. J. Classif. 34(1): 4-34 (2017) - [j21]Luis Angel García-Escudero, Alfonso Gordaliza, Francesca Greselin, Salvatore Ingrassia, Agustín Mayo-Íscar:
Robust estimation of mixtures of regressions with random covariates, via trimming and constraints. Stat. Comput. 27(2): 377-402 (2017) - 2016
- [j20]John Hinde, Salvatore Ingrassia, Tsung-I Lin, Paul D. McNicholas:
The Third Special Issue on Advances in Mixture Models. Comput. Stat. Data Anal. 93: 2-4 (2016) - [j19]Luis Angel García-Escudero, Alfonso Gordaliza, Francesca Greselin, Salvatore Ingrassia, Agustín Mayo-Íscar:
The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers. Comput. Stat. Data Anal. 99: 131-147 (2016) - [j18]Antonio Punzo, Salvatore Ingrassia:
Clustering bivariate mixed-type data via the cluster-weighted model. Comput. Stat. 31(3): 989-1013 (2016) - 2015
- [j17]Salvatore Ingrassia, Antonio Punzo, Giorgio Vittadini, Simona C. Minotti:
The Generalized Linear Mixed Cluster-Weighted Model. J. Classif. 32(1): 85-113 (2015) - [j16]Salvatore Ingrassia, Antonio Punzo, Giorgio Vittadini, Simona C. Minotti:
Erratum to: The Generalized Linear Mixed Cluster-Weighted Model. J. Classif. 32(2): 327-355 (2015) - [j15]Salvatore Ingrassia, Simona C. Minotti, Giorgio Vittadini:
Erratum to: Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions. J. Classif. 32(3): 542-543 (2015) - [j14]Francesca Greselin, Salvatore Ingrassia:
Maximum likelihood estimation in constrained parameter spaces for mixtures of factor analyzers. Stat. Comput. 25(2): 215-226 (2015) - [j13]Sanjeena Subedi, Antonio Punzo, Salvatore Ingrassia, Paul D. McNicholas:
Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction. Stat. Methods Appl. 24(4): 623-649 (2015) - 2014
- [j12]Hans-Hermann Bock, Salvatore Ingrassia, Jeroen K. Vermunt:
Special issue on "Model-based clustering and classification" (part 2). Adv. Data Anal. Classif. 8(1): 1-3 (2014) - [j11]Salvatore Ingrassia, Simona C. Minotti, Antonio Punzo:
Model-based clustering via linear cluster-weighted models. Comput. Stat. Data Anal. 71: 159-182 (2014) - 2013
- [j10]Sanjeena Subedi, Antonio Punzo, Salvatore Ingrassia, Paul D. McNicholas:
Clustering and classification via cluster-weighted factor analyzers. Adv. Data Anal. Classif. 7(1): 5-40 (2013) - [j9]Hans-Hermann Bock, Salvatore Ingrassia, Jeroen K. Vermunt:
Special issue on "Model-based clustering and classification". Adv. Data Anal. Classif. 7(3): 237-240 (2013) - [e1]Paolo Giudici, Salvatore Ingrassia, Maurizio Vichi:
Statistical Models for Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization, Springer 2013, ISBN 978-3-319-00031-2 [contents] - 2012
- [j8]Salvatore Ingrassia, Simona C. Minotti, Giorgio Vittadini:
Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions. J. Classif. 29(3): 363-401 (2012) - 2011
- [j7]Salvatore Ingrassia, Roberto Rocci:
Degeneracy of the EM algorithm for the MLE of multivariate Gaussian mixtures and dynamic constraints. Comput. Stat. Data Anal. 55(4): 1715-1725 (2011) - [j6]Francesca Greselin, Salvatore Ingrassia, Antonio Punzo:
Assessing the pattern of covariance matrices via an augmentation multiple testing procedure. Stat. Methods Appl. 20(2): 141-170 (2011) - 2010
- [j5]Francesca Greselin, Salvatore Ingrassia:
Constrained monotone EM algorithms for mixtures of multivariate t distributions. Stat. Comput. 20(1): 9-22 (2010) - [c3]Salvatore Ingrassia, Simona C. Minotti, Giuseppe Incarbone:
An EM Algorithm for the Student-t Cluster-Weighted Modeling. GfKl 2010: 13-21
2000 – 2009
- 2008
- [c2]Francesca Greselin, Salvatore Ingrassia:
Weakly Homoscedastic Constraints for Mixtures of t-Distributions. GfKl 2008: 219-228 - 2007
- [j4]Salvatore Ingrassia, Roberto Rocci:
Constrained monotone EM algorithms for finite mixture of multivariate Gaussians. Comput. Stat. Data Anal. 51(11): 5339-5351 (2007) - 2006
- [c1]Salvatore Ingrassia, Isabella Morlini:
Equivalent Number of Degrees of Freedom for Neural Networks. GfKl 2006: 229-236 - 2005
- [j3]Salvatore Ingrassia, Isabella Morlini:
Neural Network Modeling for Small Datasets. Technometrics 47(3): 297-311 (2005)
1990 – 1999
- 1998
- [j2]Angelo Gilio, Salvatore Ingrassia:
Totally coherent set-valued probability assessments. Kybernetika 34(1): 3-15 (1998) - 1993
- [j1]Salvatore Ingrassia:
Geometric Approaches to the Estimaton of the Spectral Gap of Reversible Marcov Chains. Comb. Probab. Comput. 2: 301-323 (1993)
Coauthor Index
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last updated on 2024-05-08 21:02 CEST by the dblp team
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