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Behrens-Fisher Problem
dc.contributor.advisorJurečková, Jana
dc.creatorKurková, Michaela
dc.date.accessioned2017-04-12T10:05:37Z
dc.date.available2017-04-12T10:05:37Z
dc.date.issued2008
dc.identifier.urihttp://hdl.handle.net/20.500.11956/17277
dc.description.abstractIn this work we are concerned with the problem of testing the equality of the means from the two populations for the case where the population covariance matrices are unequal. Well-known problem frequently occurring in applied statistics, called the Behrens-Fisher problem. This is widely used in economy, social sciences and medicine. We concentrate mainly on multivariate case. We study variety of possible approaches, bayesian, parametric, nonparametric, with particular solutions. At the close we mention one of possible solutions of generalized multivariate Behrens-Fisher problem, Mack-Wolfe test. A Monte Carlo simulation was conducted in order to illustrate their properties for different dimensions, the degree of heteroscedasticity, sample sizes and correlation coefficients. For comparison we mention classical two sample multivariate Hotelling T2. We demonstrate impact of nonnormality by estimating the type I error and power for selected solutions. Finally we use real data form Forest inventory in the Czech Republic 2001-2004 and we present the necessity of solution of this problem in practice.en_US
dc.languageČeštinacs_CZ
dc.language.isocs_CZ
dc.publisherUniverzita Karlova, Matematicko-fyzikální fakultacs_CZ
dc.titleBehrens-Fisherův problémcs_CZ
dc.typediplomová prácecs_CZ
dcterms.created2008
dcterms.dateAccepted2008-09-16
dc.description.departmentKatedra pravděpodobnosti a matematické statistikycs_CZ
dc.description.departmentDepartment of Probability and Mathematical Statisticsen_US
dc.description.facultyFaculty of Mathematics and Physicsen_US
dc.description.facultyMatematicko-fyzikální fakultacs_CZ
dc.identifier.repId46400
dc.title.translatedBehrens-Fisher Problemen_US
dc.contributor.refereeKalina, Jan
dc.identifier.aleph001001671
thesis.degree.nameMgr.
thesis.degree.levelnavazující magisterskécs_CZ
thesis.degree.disciplinePravděpodobnost, matematická statistika a ekonometriecs_CZ
thesis.degree.disciplineProbability, mathematical statistics and econometricsen_US
thesis.degree.programMatematikacs_CZ
thesis.degree.programMathematicsen_US
uk.thesis.typediplomová prácecs_CZ
uk.taxonomy.organization-csMatematicko-fyzikální fakulta::Katedra pravděpodobnosti a matematické statistikycs_CZ
uk.taxonomy.organization-enFaculty of Mathematics and Physics::Department of Probability and Mathematical Statisticsen_US
uk.faculty-name.csMatematicko-fyzikální fakultacs_CZ
uk.faculty-name.enFaculty of Mathematics and Physicsen_US
uk.faculty-abbr.csMFFcs_CZ
uk.degree-discipline.csPravděpodobnost, matematická statistika a ekonometriecs_CZ
uk.degree-discipline.enProbability, mathematical statistics and econometricsen_US
uk.degree-program.csMatematikacs_CZ
uk.degree-program.enMathematicsen_US
thesis.grade.csVýborněcs_CZ
thesis.grade.enExcellenten_US
uk.abstract.enIn this work we are concerned with the problem of testing the equality of the means from the two populations for the case where the population covariance matrices are unequal. Well-known problem frequently occurring in applied statistics, called the Behrens-Fisher problem. This is widely used in economy, social sciences and medicine. We concentrate mainly on multivariate case. We study variety of possible approaches, bayesian, parametric, nonparametric, with particular solutions. At the close we mention one of possible solutions of generalized multivariate Behrens-Fisher problem, Mack-Wolfe test. A Monte Carlo simulation was conducted in order to illustrate their properties for different dimensions, the degree of heteroscedasticity, sample sizes and correlation coefficients. For comparison we mention classical two sample multivariate Hotelling T2. We demonstrate impact of nonnormality by estimating the type I error and power for selected solutions. Finally we use real data form Forest inventory in the Czech Republic 2001-2004 and we present the necessity of solution of this problem in practice.en_US
uk.publication.placePrahacs_CZ
uk.grantorUniverzita Karlova, Matematicko-fyzikální fakulta, Katedra pravděpodobnosti a matematické statistikycs_CZ
dc.identifier.lisID990010016710106986


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