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Multivariate Parametric Analysis of Interval Data

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dc.contributor.authorBrito, Paula
dc.contributor.authorDuarte Silva, A. P.
dc.contributor.authorDias, José G.
dc.date.accessioned2014-06-04T09:50:39Z
dc.date.available2014-06-04T09:50:39Z
dc.date.issued2013
dc.description.abstractThis work focuses on the study of interval data, i.e., when the variables’ values are intervals of IR, using parametric probabilistic models previously proposed. These models are based on the representation of each observed interval by its MidPoint and LogRange for which multivariate Normal and Skew-Normal distributions are assumed, considering different structures of the variance-covariance matrix. The proposed modelling has been applied to different multivariate methodologies - (M)ANOVA, discriminant analysis, model-based clustering - that are presented and discussed. The R-package MAINT.Data, available on CRAN, implements models and methods for the Gaussian case.por
dc.identifier.citationBRITO, Paula; DUARTE SILVA, A.P.; DIAS, José G. - Multivariate Parametric Analysis of Interval Data. In SIS 2013 Statistical Conference on Advances in Latent Variables, Methods, Models and Applications, Brescia, Italia, 19-21 June 2013. BRENTARI, E...[et al.] (Eds.) - Advances in Latent Variables: Methods, Models and Applications. [Italia: Italian Statistical Society, 2013]. ISBN 978-88-343-2556-8. 8 p.por
dc.identifier.urihttp://hdl.handle.net/10400.14/14476
dc.language.isoengpor
dc.subjectInterval datapor
dc.subjectParametric modelling of interval datapor
dc.subjectSymbolic datapor
dc.titleMultivariate Parametric Analysis of Interval Datapor
dc.typeconference object
dspace.entity.typePublication
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor

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