Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/7129
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dc.coverage.spatialStatisticsen_US
dc.date.accessioned2013-02-28T04:46:43Z-
dc.date.available2013-02-28T04:46:43Z-
dc.date.issued2013-02-28-
dc.identifier.urihttp://hdl.handle.net/10603/7129-
dc.description.abstractThe thesis starts with a few words on Dirichlet himself. The properties of standard real type-1 and type-2 Dirichlet distributions are then discussed. Matrix-variate analogues of type-1 and type-2 Dirichlet models are also presented. A survey of some of the important areas of applications and extensions of Dirichlet models is attempted. All these are done in the first chapter. In the second chapter we introduce a new extension of type-1 Dirichlet model both in scalar variables case and in the matrix-variate case. The generalization of type-1 Dirichlet model in the scalar variables case is derived by using a property which we will call as a short memory property . Several properties of this new model, which are applicable in many fields, are presented. Here the matrix-variate analogue of an extension of a type-1 Dirichlet model is developed and its properties are also discussed. In certain studies, successive sums of variables also enter into the picture. Hence an extension of the type-2 Dirichlet model with successive sums incorporated into it, is introduced in the third chapter. Many types of properties of this new model are studied which enhance the possibility of application in different directions. Further, the matrixvariate analogue of this new model is given and its properties are also examined. The fourth chapter explores the application of a generalized real type-1 Dirichlet model in multivariate statistical analysis. It is shown that the exact null distribution of likelihood ratio criteria for testing a number of hypotheses on the parameters of one or more multivariate Gaussian populations can be obtained as a marginal distribution of this generalized Dirichlet model having a specific set of parameters. The exact distribution of the likelihood ratio criterion so obtained has a very simple and general format for every p. Various types of properties and relations involving hypergeometric series are also established.en_US
dc.format.extent91p.en_US
dc.languageEnglishen_US
dc.relation-en_US
dc.rightsuniversityen_US
dc.titleSome extensions of dirichlet models and their applicationsen_US
dc.title.alternative-en_US
dc.creator.researcherThomas, Seemonen_US
dc.subject.keywordgeometrical probabilityen_US
dc.subject.keywordgeneralized Dirichlet modelen_US
dc.subject.keywordbeta densityen_US
dc.subject.keywordshort memory propertyen_US
dc.subject.keywordneutrality principleen_US
dc.subject.keywordmatrix-variate distributionen_US
dc.subject.keywordJacobians of matrix transformationsen_US
dc.subject.keywordMeijer s G-functionen_US
dc.subject.keywordlikelihood ratio criterionen_US
dc.subject.keywordexact distributionen_US
dc.description.noteReferences given chapters wiseen_US
dc.contributor.guideThannippara, Alexen_US
dc.publisher.placeKottayamen_US
dc.publisher.universityMahatma Gandhi Universityen_US
dc.publisher.institutionDepartment of Statisticsen_US
dc.date.registeredn.d.en_US
dc.date.completed2007en_US
dc.date.awarded2008en_US
dc.format.dimensions-en_US
dc.format.accompanyingmaterialNoneen_US
dc.type.degreePh.D.en_US
dc.source.inflibnetINFLIBNETen_US
Appears in Departments:Department of Statistics

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01_title.pdfAttached File21.37 kBAdobe PDFView/Open
02_certificate.pdf27.15 kBAdobe PDFView/Open
03_declaration.pdf19.08 kBAdobe PDFView/Open
04_acknowledgements.pdf22.14 kBAdobe PDFView/Open
05_abstract.pdf32.28 kBAdobe PDFView/Open
06_contents.pdf26.92 kBAdobe PDFView/Open
07_chapter 1.pdf188.32 kBAdobe PDFView/Open
08_chapter 2.pdf226.12 kBAdobe PDFView/Open
09_chapter 3.pdf237.25 kBAdobe PDFView/Open
10_chapter 4.pdf279.04 kBAdobe PDFView/Open
11_chapter 5.pdf163.67 kBAdobe PDFView/Open


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