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Daunis i Estadella, Josep
MartÃn Fernández, Josep Antoni |
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Universitat de Girona. Departament d’Informà tica i Matemà tica Aplicada | |
Delicado, Pedro | |
Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions) Geologische Vereinigung; Institut d’EstadÃstica de Catalunya; International Association for Mathematical Geology; Cà tedra LluÃs Santaló d’Aplicacions de la Matemà tica; Generalitat de Catalunya, Departament d’Innovació, Universitats i Recerca; Ministerio de Educación y Ciencia; Ingenio 2010. |
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http://hdl.handle.net/2072/14762 | |
eng | |
Universitat de Girona. Departament d’Informà tica i Matemà tica Aplicada | |
Tots els drets reservats | |
Anà lisi funcional
EstadÃstica |
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Comparing methods for dimensionality reduction when data are density functions | |
info:eu-repo/semantics/conferenceObject | |
Recercat |