Roberto Rocci | Ricerc@Sapienza

Pubblicazioni

Titolo	Pubblicato in	Anno
Mixture of factor analyzers for mixed-type data via a composite likelihood approach	Models and Learning for Clustering and Classification	2021
Factor Uniqueness of the Structural Parafac Model	PSYCHOMETRIKA	2020
Aggregating Gaussian mixture components	book of short papers SIS2020	2020
AN INDSCAL BASED MIXTURE MODEL TO CLUSTER MIXED-TYPE OF DATA	CLADAG 2019 - Book of short papers	2019
COMPOSITE LIKELIHOOD INFERENCE FOR SIMULTANEOUS CLUSTERING AND DIMENSIONALITY REDUCTION OF MIXED-TYPE LONGITUDINAL DATA	CLADAG 2019 - Book of short papers	2019
An overview on the URV model-based approach to cluster mixed-type data	Statistical Learning of Complex Data	2019
PENALIZED VS CONSTRAINED MAXIMUM LIKELIHOOD APPROACHES FOR CLUSTERWISE LINEAR REGRESSION MODELING		2019
THE PARAFAC MODEL IN THE MAXIMUM LIKELIHOOD APPROACH		2019
Scale-constrained approaches for maximum likelihood estimation and model selection of clusterwise linear regression models	STATISTICAL METHODS & APPLICATIONS	2019
Simultaneous clustering and dimensional reduction of mixed-type data	ASMOD 2018: Proceedings of the International Conference on Advances in Statistical Modelling of Ordinal Data	2018
Simultaneous clustering and dimensional reduction of mixed-type data	11th International Conference of the ERCIM. Book of abstracts	2018
A data driven equivariant approach to constrained gaussian mixture modeling	ADVANCES IN DATA ANALYSIS AND CLASSIFICATION	2018
Some clarifications of remedies for Candecomp/Parafac degeneracy by means of an SVD-penalized approach	CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS	2017
Clusterwise linear regression modeling with soft scale constraints	INTERNATIONAL JOURNAL OF APPROXIMATE REASONING	2017
A Model-Based Approach to Simultaneous Clustering and Dimensional Reduction of Ordinal Data	PSYCHOMETRIKA	2017
Mixture models for mixed-type data through a composite likelihood approach	COMPUTATIONAL STATISTICS & DATA ANALYSIS	2017
Mixture models for simultaneous classification and reduction of three-way data	CLADAG 2017 Book of Short Papers	2017
Finite Mixture of Linear Regression Models: An Adaptive Constrained Approach to Maximum Likelihood Estimation	Soft Methods for Data Science	2017
Remedies for Degeneracy in Candecomp/Parafac	Quantitative Psychology Research	2016
Mixture models for ordinal data: a pairwise likelihood approach	STATISTICS AND COMPUTING	2016

ERC

LS2_12
PE1_14
PE6_11
SH1_6

Keywords

mixture models

Clustering and classification

Data reduction methods

latent variables

Progetti di Ricerca

New statistical learning methods for model-based unsupervised classification of complex and high dimensional data