[Forum SIS] [Convegni] Avviso seminario: Seminario 29/11 ore 11: Model-based clustering through copula

[massimo cannas]

Centro Servizi di Ateneo per la Ricerca (CeSAR)

e

Dipartimento di Scienze Economiche e Aziendali (Programma Visiting  
Professor 2018 – 2019 Dipartimento di Eccellenza)

SEMINARIO: MODEL-BASED CLUSTERING THROUGH COPULA

RELATORE: Marta Nai Ruscone,

Assistant Professor,

School of economics and management
LIUC Università Carlo Cattaneo (Castellanza)
http://my.liuc.it/persone/persona.asp?ID=1815&DAT=CV

Dipartimento di Matematica
Università degli Studi di Genova (Genova)

VENERDì 29 NOVEMBRE, ORE 11.00, AULA INFORMATICA PRESSO LA BIBLIOTECA  
DI ECONOMIA, DIPARTIMENTO DI SCIENZE ECONOPMICHE ED AZIENDALI, VIALE  
SANT'IGNAZIO 84, CAGLIARI.

ABSTRACT

Finite mixtures are applied to perform model-based clustering of  
multivariate data. Existing models are not flexible enough for  
modelling the dependence of multivariate data since they rely on  
potentially undesirable correlation restrictions and strict  
assumptions on the marginal distribution to be computationally  
tractable.

We discuss a model-based clustering method via copula to understand  
the complex and hidden dependence patterns in correlated multivariate  
data. We also propose a parsimonious version of model-based clustering  
method via /R-vine/ copula to alleviate the computational burden and  
the risk of overfitting. One of the advantages of this approach is  
that it accounts for the tail asymmetry of the data by using blocks of  
asymmetric bivariate copulas. We use simulated and real datasets to  
illustrate the proposed methodology.

BIO

Dr. Marta Nai Ruscone has a degree in Economics and Statistical  
Sciences at Università Cattolica del Sacro Cuore of Milan. Since 2015  
she is an Assistant Professor of Statistics (SECS-S/01) at the LIUC  
University of Castellanza (Italy). Starting December 2019 she will  
join the Statistics group in Genova. She has taught several bachelor,  
master and PhD courses of statistics.

Her current research interest revolves around the development of  
statistical methods based on copula function and their applications to  
multivariate data. In particular, she is interested in measures of  
association for ordinal and rank variables when the underlying  
distributions of those variables cannot be assumed to be normal. The  
main application is to the analysis and full understanding of complex  
and hidden dependence patterns in correlated multivariate data, with  
special emphasis on model-based clustering methods.

Per informazioni:

dott. Massimo Cannas
Dipartimento di Scienze Economiche e Aziendali
http://people.unica.it/massimocannas/

070-675 3410
massimo.cannas a unica.it
-- 
Massimo Cannas

Dipartimento di Scienze Economiche ed Aziendali
Università di Cagliari
Viale Sant'Ignazio 83, 09123 Cagliari
Edificio Biblioteca di Economia, studio 14
Tel: (+39) 070 675 3410
Mail: massimo.cannas a unica.it
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