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Editors-in-chief: Bettina Grün, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
movMF: An R Package for Fitting Mixtures of von Mises-Fisher Distributions | Hornik | Journal of Statistical Software
Authors: Kurt Hornik, Bettina Grün
Title: movMF: An R Package for Fitting Mixtures of von Mises-Fisher Distributions
Abstract: Finite mixtures of von Mises-Fisher distributions allow to apply model-based clustering methods to data which is of standardized length, i.e., all data points lie on the unit sphere. The R package movMF contains functionality to draw samples from ?nite mixtures of von Mises-Fisher distributions and to ?t these models using the expectation-maximization algorithm for maximum likelihood estimation. Special features are the possibility to use sparse matrix representations for the input data, different variants of the expectation-maximization algorithm, different methods for determining the concentration parameters in the M-step and to impose constraints on the concentration parameters over the components.

In this paper we describe the main ?tting function of the package and illustrate its application. In addition we compare the clustering performance of ?nite mixtures of von Mises-Fisher distributions to spherical k-means. We also discuss the resolution of several numerical issues which occur for estimating the concentration parameters and for determining the normalizing constant of the von Mises-Fisher distribution.

Page views:: 1984. Submitted: 2012-10-23. Published: 2014-07-05.
Paper: movMF: An R Package for Fitting Mixtures of von Mises-Fisher Distributions     Download PDF (Downloads: 1988)
Supplements:
movMF_0.2-0.tar.gz: R source package Download (Downloads: 262; 529KB)
v58i10.R: R example code from the paper Download (Downloads: 245; 16KB)
artificial.rda: Data in R binary format Download (Downloads: 236; 15KB)
cluto.rda: Data in R binary format Download (Downloads: 246; 8KB)

DOI: 10.18637/jss.v058.i10

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.