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dc.contributor.advisorSpurr, B. D.
dc.contributor.authorKoutbeiy, Majdi Amine
dc.coverage.spatial170 p.en_US
dc.date.accessioned2018-06-06T09:12:04Z
dc.date.available2018-06-06T09:12:04Z
dc.date.issued1990
dc.identifier.urihttps://hdl.handle.net/10023/13748
dc.description.abstractIn this thesis we compare various methods for estimating the unknown parameters in mixtures of circular and spherical distributions. We study the von Mises distribution on the circle and the Fisher distribution on the sphere. We propose a new method of estimation based on the characteristic function and compare it with the classical methods based on maximum likelihood and moments. Thus far these methods have only been successfully applied to distributions on the line. Here we show that the extension to circular and spherical distributions is reasonably straightforward and convergence to the final estimates is fairly rapid. We apply these methods to various simulated and real data sets and show that the results obtained for the mixture of two von Mises distributions are satisfactory but generally depend on the sample size and method of estimation used. However, results obtained for the mixture of two Fisher distributions show that maximum likelihood performs best overall.en_US
dc.language.isoenen_US
dc.publisherUniversity of St Andrewsen
dc.subject.lccQA276.8K7
dc.subject.lcshEstimation theoryen
dc.titleEstimating the parameters in mixtures of circular and spherical distributionsen_US
dc.typeThesisen_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US


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