dc.contributor.advisor | Pawlas, Zbyněk | |
dc.creator | Schenk, Martin | |
dc.date.accessioned | 2017-04-10T10:50:35Z | |
dc.date.available | 2017-04-10T10:50:35Z | |
dc.date.issued | 2008 | |
dc.identifier.uri | http://hdl.handle.net/20.500.11956/14895 | |
dc.description.abstract | This thesis deals with the problem of estimating the joint probability distribution of a marked process' parameters from a censored data. First, a Nelson-Aalen estimator of the cumulative hazard rate for one-dimensional case is constructed. This estimator is then smoothed by using a kernel function estimator. Then, a Kaplan-Meier estimator of the survival function is brought in. Further, a theory of set-indexed random processes is built up to be a base for the construction of a generalized Nelson-Aalen estimator of the cumulative hazard rate, which is then again smoothed. For a special case, a generalized Kaplan-Meier estimator of the multidimensional survival function is constructed. The application of the mentioned generalized estimators is shown on a particular case. These estimators are then used on simulated data. | en_US |
dc.language | English | cs_CZ |
dc.language.iso | en_US | |
dc.publisher | Univerzita Karlova, Matematicko-fyzikální fakulta | cs_CZ |
dc.title | Set-indexed stochastic processes | en_US |
dc.type | diplomová práce | cs_CZ |
dcterms.created | 2008 | |
dcterms.dateAccepted | 2008-05-15 | |
dc.description.department | Department of Probability and Mathematical Statistics | en_US |
dc.description.department | Katedra pravděpodobnosti a matematické statistiky | cs_CZ |
dc.description.faculty | Matematicko-fyzikální fakulta | cs_CZ |
dc.description.faculty | Faculty of Mathematics and Physics | en_US |
dc.identifier.repId | 46072 | |
dc.title.translated | Náhodné procesy indexované množinami | cs_CZ |
dc.contributor.referee | Rataj, Jan | |
dc.identifier.aleph | 000971332 | |
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 | Matematika | cs_CZ |
thesis.degree.program | Mathematics | en_US |
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 | Výborně | cs_CZ |
thesis.grade.en | Excellent | en_US |
uk.abstract.en | This thesis deals with the problem of estimating the joint probability distribution of a marked process' parameters from a censored data. First, a Nelson-Aalen estimator of the cumulative hazard rate for one-dimensional case is constructed. This estimator is then smoothed by using a kernel function estimator. Then, a Kaplan-Meier estimator of the survival function is brought in. Further, a theory of set-indexed random processes is built up to be a base for the construction of a generalized Nelson-Aalen estimator of the cumulative hazard rate, which is then again smoothed. For a special case, a generalized Kaplan-Meier estimator of the multidimensional survival function is constructed. The application of the mentioned generalized estimators is shown on a particular case. These estimators are then used on simulated data. | 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 | 990009713320106986 | |