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For Peer Review Only Discriminant Analysis for the von Mises-Fisher distribution Journal: Communications in Statistics - Simulation and Computation Manuscript ID: LSSP-2008-0319.R1 Manuscript Type: Original Paper Date Submitted by the Author: 11-Jul-2009 Complete List of Authors: Figueiredo, Adelaide; Faculdade de Economia da Universidade do Porto, Grupo de Matemática e Informática Keywords: Directional data, Discriminant Analysis, von Mises-Fisher distribution Abstract: The von Mises-Fisher distribution is widely used for modeling directional data. In this paper we derive the discriminant rules based on this distribution to assign objects into pre-existing classes. We determine a distance between two von Mises-Fisher populations and we calculate estimates of the misclassification probabilities. We also analyse the behavior of the distance between two von Mises-Fisher populations and of the estimates of the misclassification probabilities when we modify the parameters of the populations or the samples size or the dimension of the sphere. Finally, we present an example with real spherical data available in the literature. Note: The following files were submitted by the author for peer review, but cannot be converted to PDF. You must view these files (e.g. movies) online. DiscriminantVMisesAdelaideFigueiredo.zip URL: http://mc.manuscriptcentral.com/lssp E-mail: [email protected] Communications in Statistics - Simulation and Computation

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Discriminant Analysis for the von Mises-Fisher distribution

Journal: Communications in Statistics - Simulation and Computation

Manuscript ID: LSSP-2008-0319.R1

Manuscript Type: Original Paper

Date Submitted by the Author:

11-Jul-2009

Complete List of Authors: Figueiredo, Adelaide; Faculdade de Economia da Universidade do Porto, Grupo de Matemática e Informática

Keywords: Directional data, Discriminant Analysis, von Mises-Fisher distribution

Abstract:

The von Mises-Fisher distribution is widely used for modeling directional data. In this paper we derive the discriminant rules based on this distribution to assign objects into pre-existing classes. We determine a distance between two von Mises-Fisher populations and we calculate estimates of the misclassification probabilities. We also analyse the behavior of the distance between two von Mises-Fisher populations and of the estimates of the misclassification probabilities when we modify the parameters of the populations or the samples size or the dimension of the sphere. Finally, we present an example with real spherical data available in the literature.

Note: The following files were submitted by the author for peer review, but cannot be converted to PDF. You must view these files (e.g. movies) online.

DiscriminantVMisesAdelaideFigueiredo.zip

URL: http://mc.manuscriptcentral.com/lssp E-mail: [email protected]

Communications in Statistics - Simulation and Computation

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