A semi-parametric model for circular data based on mixtures of beta distributions

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dc.contributor.author Carnicero, José Antonio
dc.contributor.author Wiper, Michael Peter
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2008-04-08T07:58:47Z
dc.date.available 2008-04-08T07:58:47Z
dc.date.issued 2008-03
dc.identifier.uri http://hdl.handle.net/10016/2362
dc.description.abstract This paper introduces a new, semi-parametric model for circular data, based on mixtures of shifted, scaled, beta (SSB) densities. This model is more general than the Bernstein polynomial density model which is well known to provide good approximations to any density with finite support and it is shown that, as for the Bernstein polynomial model, the trigonometric moments of the SSB mixture model can all be derived. Two methods of fitting the SSB mixture model are considered. Firstly, a classical, maximum likelihood approach for fitting mixtures of a given number of SSB components is introduced. The Bayesian information criterion is then used for model selection. Secondly, a Bayesian approach using Gibbs sampling is considered. In this case, the number of mixture components is selected via an appropriate deviance information criterion. Both approaches are illustrated with real data sets and the results are compared with those obtained using Bernstein polynomials and mixtures of von Mises distributions.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 08-05
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Circular data
dc.subject.other Shifted, scaled, beta distribution
dc.subject.other Mixture models
dc.subject.other Bernstein polynomials
dc.title A semi-parametric model for circular data based on mixtures of beta distributions
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws081305
dc.affiliation.dpto UC3M. Departamento de Estadística
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