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Estimators of variance function in nonparametric regression
dc.contributor.advisorHušková, Marie
dc.creatorHyklová, Bronislava
dc.date.accessioned2017-03-31T09:46:11Z
dc.date.available2017-03-31T09:46:11Z
dc.date.issued2007
dc.identifier.urihttp://hdl.handle.net/20.500.11956/8162
dc.description.abstractThe thesis studies variance function estimation in nonparametric regression model. It focuses on local polynomial estimators particularly. Exact expressions of conditional variance function estimator bias and covariance are derived and important asymptotical aproximations of these characteristics are also provided. Further the EBBS method for bandwidth selection and Dette's homoscedasticity test are described. Results of Prague Klementinum data processing are presented at the end of the thesis.en_US
dc.languageČeštinacs_CZ
dc.language.isocs_CZ
dc.publisherUniverzita Karlova, Matematicko-fyzikální fakultacs_CZ
dc.titleOdhady varianční funkce v neparametrických regresních modelechcs_CZ
dc.typediplomová prácecs_CZ
dcterms.created2007
dcterms.dateAccepted2007-02-05
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.repId42159
dc.title.translatedEstimators of variance function in nonparametric regressionen_US
dc.contributor.refereeAntoch, Jaromír
dc.identifier.aleph000850326
thesis.degree.nameMgr.
thesis.degree.levelmagisterskécs_CZ
thesis.degree.disciplineUčitelství matematiky pro střední školy v kombinaci s odbornou matematikoucs_CZ
thesis.degree.disciplineProgram for future teachers of mathematics for high schools in combination with professional mathematicsen_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.csUčitelství matematiky pro střední školy v kombinaci s odbornou matematikoucs_CZ
uk.degree-discipline.enProgram for future teachers of mathematics for high schools in combination with professional mathematicsen_US
uk.degree-program.csMatematikacs_CZ
uk.degree-program.enMathematicsen_US
thesis.grade.csVelmi dobřecs_CZ
thesis.grade.enVery gooden_US
uk.abstract.enThe thesis studies variance function estimation in nonparametric regression model. It focuses on local polynomial estimators particularly. Exact expressions of conditional variance function estimator bias and covariance are derived and important asymptotical aproximations of these characteristics are also provided. Further the EBBS method for bandwidth selection and Dette's homoscedasticity test are described. Results of Prague Klementinum data processing are presented at the end of the thesis.en_US
uk.publication.placePrahacs_CZ
uk.grantorUniverzita Karlova, Matematicko-fyzikální fakulta, Katedra pravděpodobnosti a matematické statistikycs_CZ
dc.identifier.lisID990008503260106986


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