dc.contributor.advisor | Maciak, Matúš | |
dc.creator | Šimičák, Jakub | |
dc.date.accessioned | 2023-11-06T16:24:43Z | |
dc.date.available | 2023-11-06T16:24:43Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/20.500.11956/184597 | |
dc.description.abstract | The purpose of the bachelor thesis is to introduce the reader to two approaches to the construction of prediction intervals. The first procedure assumes a probabilistic model and leads to a frequentist prediction interval that uses the relevant theoretical quantiles of probability distributions. The second procedure assumes no probabilistic model and leads to a conformal prediction interval that uses empirical quantiles of the relevant random sample. In the course of the paper, both approaches will be derived in general terms and then illustrated with concrete examples. The thesis also includes a simulation study comparing the empirical coverage of frequentist and conformal prediction inter- vals for random selections from different distributions. 1 | en_US |
dc.language | Slovenčina | cs_CZ |
dc.language.iso | sk_SK | |
dc.publisher | Univerzita Karlova, Matematicko-fyzikální fakulta | cs_CZ |
dc.subject | theoretical quantile|empirický kvantil|predikční interval|spolehlivost | cs_CZ |
dc.subject | theoretical quantile|empirical quantile|prediction interval|confidence | en_US |
dc.title | Teoretické a empirické kvantily a ich využitie pri konštrukcií predikčných intervalov | sk_SK |
dc.type | bakalářská práce | cs_CZ |
dcterms.created | 2023 | |
dcterms.dateAccepted | 2023-09-08 | |
dc.description.department | Katedra pravděpodobnosti a matematické statistiky | cs_CZ |
dc.description.department | Department of Probability and Mathematical Statistics | en_US |
dc.description.faculty | Matematicko-fyzikální fakulta | cs_CZ |
dc.description.faculty | Faculty of Mathematics and Physics | en_US |
dc.identifier.repId | 260195 | |
dc.title.translated | Theoretical and empirical quantiles and their use for prediction interval construction | en_US |
dc.title.translated | Teoretické a empirické kvantily a jejích využití pro konstrukci predikčních intervalů | cs_CZ |
dc.contributor.referee | Omelka, Marek | |
thesis.degree.name | Bc. | |
thesis.degree.level | bakalářské | cs_CZ |
thesis.degree.discipline | Finanční matematika | cs_CZ |
thesis.degree.discipline | Financial Mathematics | en_US |
thesis.degree.program | Matematika | cs_CZ |
thesis.degree.program | Mathematics | en_US |
uk.thesis.type | bakalářská 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 | Finanční matematika | cs_CZ |
uk.degree-discipline.en | Financial Mathematics | en_US |
uk.degree-program.cs | Matematika | cs_CZ |
uk.degree-program.en | Mathematics | en_US |
thesis.grade.cs | Dobře | cs_CZ |
thesis.grade.en | Good | en_US |
uk.abstract.en | The purpose of the bachelor thesis is to introduce the reader to two approaches to the construction of prediction intervals. The first procedure assumes a probabilistic model and leads to a frequentist prediction interval that uses the relevant theoretical quantiles of probability distributions. The second procedure assumes no probabilistic model and leads to a conformal prediction interval that uses empirical quantiles of the relevant random sample. In the course of the paper, both approaches will be derived in general terms and then illustrated with concrete examples. The thesis also includes a simulation study comparing the empirical coverage of frequentist and conformal prediction inter- vals for random selections from different distributions. 1 | en_US |
uk.file-availability | V | |
uk.grantor | Univerzita Karlova, Matematicko-fyzikální fakulta, Katedra pravděpodobnosti a matematické statistiky | cs_CZ |
thesis.grade.code | 3 | |
uk.publication-place | Praha | cs_CZ |
uk.thesis.defenceStatus | O | |