Analysis of circular data in the dynamic model and mixture of von Mises distributions

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dc.contributor.advisorCarvalho, Carlos Marinho, 1978-
dc.creatorLan, Tian, active 2013en
dc.date.accessioned2013-12-10T15:31:23Zen
dc.date.accessioned2017-05-11T22:39:57Z
dc.date.available2017-05-11T22:39:57Z
dc.date.issued2013-05en
dc.date.submittedMay 2013en
dc.date.updated2013-12-10T15:31:23Zen
dc.descriptiontexten
dc.description.abstractAnalysis of circular data becomes more and more popular in many fields of studies. In this report, I present two statistical analysis of circular data using von Mises distributions. Firstly, the maximization-expectation algorithm is reviewed and used to classify and estimate circular data from the mixture of von Mises distributions. Secondly, Forward Filtering Backward Smoothing method via particle filtering is reviewed and implemented when circular data appears in the dynamic state-space models.en
dc.description.departmentStatisticsen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/22608en
dc.language.isoen_USen
dc.subjectCircular dataen
dc.subjectVon Mises distributionen
dc.subjectMixture of distributionsen
dc.subjectTime seriesen
dc.subjectDynamic modelen
dc.subjectExpectation-maximization algorithmen
dc.subjectParticle filteren
dc.titleAnalysis of circular data in the dynamic model and mixture of von Mises distributionsen

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