Sfoglia per Autore
Mixture models for mixed-type data through a pairwise likelihood approach
2014 Ranalli, M; Rocci, R
Handbook of Cluster Analysis
2015 Hennig, C; Meila, M; Murtagh, F; Rocci, R
Clustering Methods for Ordinal Data: A Comparison Between Standard and New Approaches
2015 Ranalli, Monia; Rocci, Roberto
Remedies for Degeneracy in Candecomp/Parafac
2016 Giordani, Paolo; Rocci, Roberto
Standard and novel model selection criteria in the pairwise likelihood estimation of a mixture model for ordinal data
2016 Ranalli, M.; Rocci, R.
Mixture models for ordinal data: a pairwise likelihood approach
2016 Ranalli, M.; Rocci, R.
Mixture models for simultaneous classification and reduction of three-way data
2017 Rocci, Roberto; Vichi, Maurizio; Ranalli, Monia
A Model-Based Approach to Simultaneous Clustering and Dimensional Reduction of Ordinal Data
2017 Ranalli, M.; Rocci, R.
Finite Mixture of Linear Regression Models: An Adaptive Constrained Approach to Maximum Likelihood Estimation
2017 Di Mari, Roberto; Rocci, Roberto; Antonio Gattone, Stefano
Clusterwise linear regression modeling with soft scale constraints
2017 Di Mari, R; Rocci, R; Gattone, Sa
Mixture models for mixed-type data through a composite likelihood approach
2017 Ranalli, M.; Rocci, R.
Some clarifications of remedies for Candecomp/Parafac degeneracy by means of an SVD-penalized approach
2017 Giordani, Paolo; Rocci, Roberto
Simultaneous clustering and dimensional reduction of mixed-type data
2018 Ranalli, Monia; Rocci, Roberto
Simultaneous clustering and dimensional reduction of mixed-type data
2018 Ranalli, Monia; Rocci, Roberto
A data driven equivariant approach to constrained gaussian mixture modeling
2018 Rocci, R.; Gattone, S. A.; Di Mari, R.
PENALIZED VS CONSTRAINED MAXIMUM LIKELIHOOD APPROACHES FOR CLUSTERWISE LINEAR REGRESSION MODELING
2019 Di Mari, Roberto; Antonio Gattone, Stefano; Rocci, Roberto
AN INDSCAL BASED MIXTURE MODEL TO CLUSTER MIXED-TYPE OF DATA
2019 Rocci, Roberto; Ranalli, Monia
THE PARAFAC MODEL IN THE MAXIMUM LIKELIHOOD APPROACH
2019 Giordani, Paolo; Rocci, Roberto; Bove, Giuseppe
An overview on the URV model-based approach to cluster mixed-type data
2019 Ranalli, M.; Rocci, R.
Scale-constrained approaches for maximum likelihood estimation and model selection of clusterwise linear regression models
2019 Di Mari, Roberto; Rocci, Roberto; Gattone Stefano, Antonio
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