Salvatore Ingrassia
Salvatore Ingrassia
Full Professor of Statistics, Università di Catania (Italy)
Verified email at unict.it - Homepage
Title
Cited by
Cited by
Year
Constrained monotone EM algorithms for finite mixture of multivariate Gaussians
S Ingrassia, R Rocci
Computational Statistics & Data Analysis 51 (11), 5339-5351, 2007
982007
Local statistical modeling via a cluster-weighted approach with elliptical distributions
S Ingrassia, SC Minotti, G Vittadini
Journal of classification 29 (3), 363-401, 2012
792012
A likelihood-based constrained algorithm for multivariate normal mixture models
S Ingrassia
Statistical Methods and Applications 13 (2), 151-166, 2004
702004
Model-based clustering via linear cluster-weighted models
S Ingrassia, SC Minotti, A Punzo
Computational Statistics & Data Analysis 71, 159-182, 2014
592014
On the rate of convergence of the Metropolis algorithm and Gibbs sampler by geometric bounds
S Ingrassia
The Annals of Applied Probability, 347-389, 1994
531994
Clustering and classification via cluster-weighted factor analyzers
S Subedi, A Punzo, S Ingrassia, PD Mcnicholas
Advances in Data Analysis and Classification 7 (1), 5-40, 2013
502013
Constrained monotone EM algorithms for mixtures of multivariate t distributions
F Greselin, S Ingrassia
Statistics and computing 20 (1), 9-22, 2010
502010
Erratum to: The generalized linear mixed cluster-weighted model
S Ingrassia, A Punzo, G Vittadini, SC Minotti
Journal of Classification 32 (2), 327-355, 2015
442015
Neural network modeling for small datasets
S Ingrassia, I Morlini
Technometrics 47 (3), 297-311, 2005
442005
Cluser-weighed $$$$-facor analyzers for robus model-based clusering and dimension reducion
S Subedi, A Punzo, S Ingrassia, PD McNicholas
Statistical Methods & Applications 24 (4), 623-649, 2015
342015
Degeneracy of the EM algorithm for the MLE of multivariate Gaussian mixtures and dynamic constraints
S Ingrassia, R Rocci
Computational statistics & data analysis 55 (4), 1715-1725, 2011
332011
Totally coherent set-valued probability assessments
A Gilio, S Ingrassia
Kybernetika 34 (1), [3]-15, 1998
281998
Functional principal component analysis of financial time series
S Ingrassia, GD Costanzo
New Developments in Classification and Data Analysis, 351-358, 2005
252005
Multivariate response and parsimony for Gaussian cluster-weighted models
UJ Dang, A Punzo, PD McNicholas, S Ingrassia, RP Browne
Journal of Classification 34 (1), 4-34, 2017
232017
Clustering bivariate mixed-type data via the cluster-weighted model
A Punzo, S Ingrassia
Computational Statistics 31 (3), 989-1013, 2016
222016
A comparison between the simulated annealing and the EM algorithms in normal mixture decompositions
S Ingrassia
Statistics and Computing 2 (4), 203-211, 1992
201992
The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers
LA García-Escudero, A Gordaliza, F Greselin, S Ingrassia, A Mayo-Iscar
Computational Statistics & Data Analysis 99, 131-147, 2016
172016
flexCWM: a flexible framework for cluster-weighted models
A Mazza, A Punzo, S Ingrassia
J Stat Softw 86 (2), 1-30, 2018
152018
The effect of ISM absorption on stellar activity measurements and its relevance for exoplanet studies
L Fossati, SE Marcelja, D Staab, PE Cubillos, K France, CA Haswell, ...
Astronomy & Astrophysics 601, A104, 2017
152017
Maximum likelihood estimation in constrained parameter spaces for mixtures of factor analyzers
F Greselin, S Ingrassia
Statistics and Computing 25 (2), 215-226, 2015
152015
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