A comparison of the alr and ilr transformations for kernel density estimation of compositional data

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dc.contributor Universitat de Girona. Departament d'Informàtica i Matemàtica Aplicada
dc.contributor.author Chacón, J.E.
dc.contributor.author Martín Fernández, Josep Antoni
dc.contributor.author Mateu i Figueras, Glòria
dc.contributor.editor Daunis i Estadella, Josep
dc.contributor.editor Martín Fernández, Josep Antoni
dc.date.issued 2008-05-29
dc.identifier.citation Chacón, J.E.; MArtín Fernández, J.A.; Mateu i Figueras, G. 'A comparison of the alr and ilr transformations for kernel density estimation of compositional data' a CODAWORK’08. Girona: La Universitat, 2008 [consulta: 13 maig 2008]. Necessita Adobe Acrobat. Disponible a Internet a: http://hdl.handle.net/10256/724
dc.identifier.uri http://hdl.handle.net/10256/724
dc.description.abstract In a seminal paper, Aitchison and Lauder (1985) introduced classical kernel density estimation techniques in the context of compositional data analysis. Indeed, they gave two options for the choice of the kernel to be used in the kernel estimator. One of these kernels is based on the use the alr transformation on the simplex SD jointly with the normal distribution on RD-1. However, these authors themselves recognized that this method has some deficiencies. A method for overcoming these dificulties based on recent developments for compositional data analysis and multivariate kernel estimation theory, combining the ilr transformation with the use of the normal density with a full bandwidth matrix, was recently proposed in Martín-Fernández, Chacón and Mateu- Figueras (2006). Here we present an extensive simulation study that compares both methods in practice, thus exploring the finite-sample behaviour of both estimators
dc.description.sponsorship Geologische Vereinigung; Institut d’Estadística de Catalunya; International Association for Mathematical Geology; Càtedra Lluís Santaló d’Aplicacions de la Matemàtica; Generalitat de Catalunya, Departament d’Innovació, Universitats i Recerca; Ministerio de Educación y Ciencia; Ingenio 2010.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada
dc.rights Tots els drets reservats
dc.subject Correlació (Estadística)
dc.subject Anàlisi multivariable
dc.subject Kernel, Funcions de
dc.title A comparison of the alr and ilr transformations for kernel density estimation of compositional data
dc.type info:eu-repo/semantics/conferenceObject

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