Geometric Approaches to the Estimaton of the Spectral Gap of Reversible Marcov Chains. - Salvatore Ingrassia (Comb. Probab. Comput., 1993)

Totally coherent set-valued probability assessments. - Angelo Gilio; Salvatore Ingrassia (Kybernetika, 1998)

Neural Network Modeling for Small Datasets. - Salvatore Ingrassia; Isabella Morlini (Technometrics, 2005)

Equivalent Number of Degrees of Freedom for Neural Networks. - Salvatore Ingrassia; Isabella Morlini (GfKl, 2006)

Constrained monotone EM algorithms for finite mixture of multivariate Gaussians. - Salvatore Ingrassia; Roberto Rocci (Comput. Stat. Data Anal., 2007)

Weakly Homoscedastic Constraints for Mixtures of t-Distributions. - Francesca Greselin; Salvatore Ingrassia (GfKl, 2008)

An EM Algorithm for the Student-t Cluster-Weighted Modeling. - Salvatore Ingrassia; Simona C. Minotti; Giuseppe Incarbone (GfKl, 2010)

Constrained monotone EM algorithms for mixtures of multivariate t distributions. - Francesca Greselin; Salvatore Ingrassia (Stat. Comput., 2010)

Degeneracy of the EM algorithm for the MLE of multivariate Gaussian mixtures and dynamic constraints. - Salvatore Ingrassia; Roberto Rocci (Comput. Stat. Data Anal., 2011)

Assessing the pattern of covariance matrices via an augmentation multiple testing procedure. - Francesca Greselin; Salvatore Ingrassia; Antonio Punzo (Stat. Methods Appl., 2011)

Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions. - Salvatore Ingrassia; Simona C. Minotti; Giorgio Vittadini (J. Classif., 2012)

Special issue on "Model-based clustering and classification". - Hans-Hermann Bock; Salvatore Ingrassia; Jeroen K. Vermunt (Adv. Data Anal. Classif., 2013)

Clustering and classification via cluster-weighted factor analyzers. - Sanjeena Subedi; Antonio Punzo; Salvatore Ingrassia; Paul D. McNicholas (Adv. Data Anal. Classif., 2013)

Special issue on "Model-based clustering and classification" (part 2). - Hans-Hermann Bock; Salvatore Ingrassia; Jeroen K. Vermunt (Adv. Data Anal. Classif., 2014)

Model-based clustering via linear cluster-weighted models. - Salvatore Ingrassia; Simona C. Minotti; Antonio Punzo (Comput. Stat. Data Anal., 2014)

Erratum to: Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions. - Salvatore Ingrassia; Simona C. Minotti; Giorgio Vittadini (J. Classif., 2015)

The Generalized Linear Mixed Cluster-Weighted Model. - Salvatore Ingrassia; Antonio Punzo; Giorgio Vittadini; Simona C. Minotti (J. Classif., 2015)

Erratum to: The Generalized Linear Mixed Cluster-Weighted Model. - Salvatore Ingrassia; Antonio Punzo; Giorgio Vittadini; Simona C. Minotti (J. Classif., 2015)

Maximum likelihood estimation in constrained parameter spaces for mixtures of factor analyzers. - Francesca Greselin; Salvatore Ingrassia (Stat. Comput., 2015)

Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction. - Sanjeena Subedi; Antonio Punzo; Salvatore Ingrassia; Paul D. McNicholas (Stat. Methods Appl., 2015)

The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers. - Luis Angel García-Escudero; Alfonso Gordaliza; Francesca Greselin; Salvatore Ingrassia; Agustín Mayo-Íscar (Comput. Stat. Data Anal., 2016)

The Third Special Issue on Advances in Mixture Models. - John Hinde; Salvatore Ingrassia; Tsung-I Lin; Paul D. McNicholas (Comput. Stat. Data Anal., 2016)

Clustering bivariate mixed-type data via the cluster-weighted model. - Antonio Punzo; Salvatore Ingrassia (Comput. Stat., 2016)

Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models. - Utkarsh J. Dang; Antonio Punzo; Paul D. McNicholas; Salvatore Ingrassia; Ryan P. Browne (J. Classif., 2017)

Robust estimation of mixtures of regressions with random covariates, via trimming and constraints. - Luis Angel García-Escudero; Alfonso Gordaliza; Francesca Greselin; Salvatore Ingrassia; Agustín Mayo-Íscar (Stat. Comput., 2017)

Eigenvalues and constraints in mixture modeling: geometric and computational issues. - Luis Angel García-Escudero; Alfonso Gordaliza; Francesca Greselin; Salvatore Ingrassia; Agustín Mayo-Íscar (Adv. Data Anal. Classif., 2018)

Special issue on "Advances on model-based clustering and classification" - Preface by the Guest Editors. - Sylvia Frühwirth-Schnatter; Salvatore Ingrassia; Agustín Mayo-Íscar (Adv. Data Anal. Classif., 2019)

Editorial for the 4th Special Issue on advances in mixture models. - Jochen Einbeck; John Hinde; Salvatore Ingrassia; Tsung-I Lin; Paul D. McNicholas (Comput. Stat. Data Anal., 2019)

Special issue on "Innovations on model based clustering and classification". - Christophe Biernacki; Luis Angel García-Escudero; Salvatore Ingrassia (Adv. Data Anal. Classif., 2020)

Cluster Validation for Mixtures of Regressions via the Total Sum of Squares Decomposition. - Salvatore Ingrassia; Antonio Punzo (J. Classif., 2020)

On parsimonious models for modeling matrix data. - Shuchismita Sarkar; Xuwen Zhu; Volodymyr Melnykov; Salvatore Ingrassia (Comput. Stat. Data Anal., 2020)

A Graphical Approach for the Selection of the Number of Clusters in the Spectral Clustering Algorithm. - Cinzia Di Nuzzo; Salvatore Ingrassia (SIS, 2021)

Editorial for ADAC issue 1 of volume 16 (2022). - Salvatore Ingrassia; Julien Jacques; Weixin Yao (Adv. Data Anal. Classif., 2022)

Special issue on "Models and learning for clustering and Classification". - Salvatore Ingrassia; Julien Jacques; Weixin Yao (Adv. Data Anal. Classif., 2022)

Local and Overall Deviance R-Squared Measures for Mixtures of Generalized Linear Models. - Roberto Di Mari; Salvatore Ingrassia; Antonio Punzo (J. Classif., 2023)

Special issue on "advances in models and learning for clustering and classification". - Luis Angel García-Escudero; Salvatore Ingrassia; Thomas Brendan Murphy (Adv. Data Anal. Classif., 2024)

An EM algorithm for fitting matrix-variate normal distributions on interval-censored and missing data. - Victor H. Lachos; Salvatore D. Tomarchio; Antonio Punzo; Salvatore Ingrassia (Stat. Comput., 2025)