Recombining partitions via unimodality tests

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dc.contributor.author Álvarez, Adolfo
dc.contributor.author Peña, Daniel
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2014-04-02T14:00:53Z
dc.date.available 2014-04-02T14:00:53Z
dc.date.issued 2013-03
dc.identifier.uri http://hdl.handle.net/10016/18706
dc.description.abstract In this article we propose a recombination procedure for previously split data. It is basedon the study of modes in the density of the data, since departing from unimodality canbe a sign of the presence of clusters. We develop an algorithm that integrates a splitting process inherited from the SAR algorithm (Peña et al., 2004) with unimodality tests such as the dip test proposed by Hartigan and Hartigan (1985), and finally, we use anetwork configuration to visualize the results. We show that this can be a useful tool to detect heterogeneity in the data, but limited to univariate data because of the nature of the dip test. In a second stage we discuss the use of multivariate mode detection tests to avoid dimensionality reduction techniques such as projecting multivariate data into one dimension. The results of the application of multivariate unimodality tests show that is possible to detect the cluster structure of the data, although more research can be oriented to estimate the proper fine-tuning of some parameters of the test for a given dataset or distribution.
dc.description.sponsorship Work partially supported by Spanish Ministry of Science and Innovation, research projects SEJ2007-64500 and ECO2012-38442
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries Statistics and Econometrics Series
dc.relation.ispartofseries 13-07
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Cluster analysis
dc.subject.other Unimodality
dc.subject.other Dip test
dc.title Recombining partitions via unimodality tests
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. ECO2012-38442
dc.type.version submitedVersion
dc.identifier.uxxi DT/0000001189
dc.identifier.repec ws130706
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