Particular emphasis has been put, lately, on the analysis of categorical data and many proposals have appeared, ranging from pure methodological contributions to more applicative ones. Among such proposals, the CUB class of distributions, a mixture model for the analysis of ordinal data that has been successfully employed in various fields, seems of particular interest. CUB are univariate models that do not possess, at present, a multivariate version: aim of the present work is to investigate the feasibility of building a higher-dimensional version of such models and its possible applications. In order to achieve such results, we propose to employ techniques typical of the framework of copula models, that have proven to be valid tools for multivariate models construction and data analysis

A proposal for the multidimensional extension of CUB models / F. Andreis, P.A. Ferrari - In: Cladag 2013 : 9th meeting of the classification and data analysis group : book of abstracts / [a cura di] T. Minerva, I. Morlini, F. Palumbo. - Padova : CLEUP, 2013. - ISBN 9788867871179. - pp. 15-18 (( Intervento presentato al 9. convegno Scientific meeting of the classification and data analysis gGroup tenutosi a Modena nel 2013.

A proposal for the multidimensional extension of CUB models

F. Andreis
Primo
;
P.A. Ferrari
Secondo
2013

Abstract

Particular emphasis has been put, lately, on the analysis of categorical data and many proposals have appeared, ranging from pure methodological contributions to more applicative ones. Among such proposals, the CUB class of distributions, a mixture model for the analysis of ordinal data that has been successfully employed in various fields, seems of particular interest. CUB are univariate models that do not possess, at present, a multivariate version: aim of the present work is to investigate the feasibility of building a higher-dimensional version of such models and its possible applications. In order to achieve such results, we propose to employ techniques typical of the framework of copula models, that have proven to be valid tools for multivariate models construction and data analysis
Multivariate ordinal data ; CUB models ; Copula models ; Dependence structures
Settore SECS-S/01 - Statistica
2013
Società italiana di Statistica
http://www.cladag2013.it/images/file/CLADAG2013_Abstract.pdf
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/232348
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