Mardia, KV and Voss, J (2014) Some Fundamental Properties of Multivariate von Mises Distributions. Communications in Statistics — Theory and Methods, 43 (6). 1132 - 1144. ISSN 0361-0926
Abstract
In application areas like bioinformatics, multivariate distributions on angles are encountered which show significant clustering. One approach to statistical modeling of such situations is to use mixtures of unimodal distributions. In the literature (Mardia et al., 2012), the multivariate von Mises distribution, also known as the multivariate sine distribution, has been suggested for components of such models, but work in the area has been hampered by the fact that no good criteria for the von Mises distribution to be unimodal were available. In this article we study the question about when a multivariate von Mises distribution is unimodal. We give sufficient criteria for this to be the case and show examples of distributions with multiple modes when these criteria are violated. In addition, we propose a method to generate samples from the von Mises distribution in the case of high concentration.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2014, Taylor & Francis Group, LLC. This is an Accepted Manuscript of an article published by Taylor & Francis in Communications in Statistics - Theory and Methods on 4 March 2014, available online: http://dx.doi.org/10.1080/03610926.2012.670353 |
Keywords: | Bioinformatics; Directional distributions; Mixture models; Modes;Simulation; Sine distribution |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Sep 2015 15:33 |
Last Modified: | 17 Jan 2018 15:42 |
Published Version: | http://dx.doi.org/10.1080/03610926.2012.670353 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/03610926.2012.670353 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:89864 |