| dc.contributor.advisor | Hlubinka, Daniel | |
| dc.creator | Ivanková, Kristýna | |
| dc.date.accessioned | 2017-04-13T09:24:15Z | |
| dc.date.available | 2017-04-13T09:24:15Z | |
| dc.date.issued | 2009 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11956/18944 | |
| dc.description.abstract | This work considers various approaches for modelling multivariate extremal events. First we review theory in the univariate case| the Fisher-Tippett theorem and the generalized Pareto distribution. We proceed with an extension to the multivariate case using the spectral measure and point processes for modelling dependence between components, ending with a review of parametric dependence models and ways to t them to data. We compare these classical methods to a new semi-parametric conditional approach. Finally, we apply the discussed methods in a simulation and on a dataset, compare the results and highlight classes of problems that the various approaches are suitable to. | en_US |
| dc.language | English | cs_CZ |
| dc.language.iso | en_US | |
| dc.publisher | Univerzita Karlova, Matematicko-fyzikální fakulta | cs_CZ |
| dc.title | Multivariate Extremes | en_US |
| dc.type | diplomová práce | cs_CZ |
| dcterms.created | 2009 | |
| dcterms.dateAccepted | 2009-02-06 | |
| dc.description.department | Department of Probability and Mathematical Statistics | en_US |
| dc.description.department | Katedra pravděpodobnosti a matematické statistiky | cs_CZ |
| dc.description.faculty | Faculty of Mathematics and Physics | en_US |
| dc.description.faculty | Matematicko-fyzikální fakulta | cs_CZ |
| dc.identifier.repId | 46294 | |
| dc.title.translated | Vícerozměrné extrémy | cs_CZ |
| dc.contributor.referee | Kaňková, Vlasta | |
| dc.identifier.aleph | 001037970 | |
| thesis.degree.name | Mgr. | |
| thesis.degree.level | navazující magisterské | cs_CZ |
| thesis.degree.discipline | Probability, mathematical statistics and econometrics | en_US |
| thesis.degree.discipline | Pravděpodobnost, matematická statistika a ekonometrie | cs_CZ |
| thesis.degree.program | Mathematics | en_US |
| thesis.degree.program | Matematika | cs_CZ |
| uk.thesis.type | diplomová práce | cs_CZ |
| uk.taxonomy.organization-cs | Matematicko-fyzikální fakulta::Katedra pravděpodobnosti a matematické statistiky | cs_CZ |
| uk.taxonomy.organization-en | Faculty of Mathematics and Physics::Department of Probability and Mathematical Statistics | en_US |
| uk.faculty-name.cs | Matematicko-fyzikální fakulta | cs_CZ |
| uk.faculty-name.en | Faculty of Mathematics and Physics | en_US |
| uk.faculty-abbr.cs | MFF | cs_CZ |
| uk.degree-discipline.cs | Pravděpodobnost, matematická statistika a ekonometrie | cs_CZ |
| uk.degree-discipline.en | Probability, mathematical statistics and econometrics | en_US |
| uk.degree-program.cs | Matematika | cs_CZ |
| uk.degree-program.en | Mathematics | en_US |
| thesis.grade.cs | Velmi dobře | cs_CZ |
| thesis.grade.en | Very good | en_US |
| uk.abstract.en | This work considers various approaches for modelling multivariate extremal events. First we review theory in the univariate case| the Fisher-Tippett theorem and the generalized Pareto distribution. We proceed with an extension to the multivariate case using the spectral measure and point processes for modelling dependence between components, ending with a review of parametric dependence models and ways to t them to data. We compare these classical methods to a new semi-parametric conditional approach. Finally, we apply the discussed methods in a simulation and on a dataset, compare the results and highlight classes of problems that the various approaches are suitable to. | en_US |
| uk.file-availability | V | |
| uk.publication.place | Praha | cs_CZ |
| uk.grantor | Univerzita Karlova, Matematicko-fyzikální fakulta, Katedra pravděpodobnosti a matematické statistiky | cs_CZ |
| dc.identifier.lisID | 990010379700106986 | |
