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13.557 Articles in journals published by the UPC
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A comparison of computational approaches for maximum likelihood estimation of the Dirichlet parameters on high-dimensional data

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Giordan, Marco
Wehrens, Ron
Document typeArticle
Defense date2015-06
PublisherInstitut d'Estadística de Catalunya
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Likelihood estimates of the Dirichlet distribution parameters can be obtained only through numerical algorithms. Such algorithms can provide estimates outside the correct range for the parameters and/or can require a large amount of iterations to reach convergence. These problems can be aggravated if good starting values are not provided. In this paper we discuss several approaches that can partially avoid these problems providing a good trade-off between efficiency and stability. The performances of these approaches are compared on high-dimensional real and simulated data.
CitationGiordan, Marco; Wehrens, Ron. A comparison of computational approaches for maximum likelihood estimation of the Dirichlet parameters on high-dimensional data. "SORT", Juny 2015, vol. 39, p. 109-126. 
URIhttp://hdl.handle.net/2117/88522
ISSN1696-2281
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