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Nonparametric smoothing in extreme value theory
Includes bibliographical references (leaves 137-138).
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Statistical Sciences
2014
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| _version_ | 1867613151190581248 |
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| access_status_str | Open Access |
| author | Clur, John-Craig |
| author2 | Haines, Linda |
| author_browse | Clur, John-Craig Haines, Linda |
| author_facet | Haines, Linda Clur, John-Craig |
| author_sort | Clur, John-Craig |
| collection | Thesis |
| description | Includes bibliographical references (leaves 137-138). |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/10285 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:31:34.243Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/10285 Nonparametric smoothing in extreme value theory Clur, John-Craig Haines, Linda Financial Mathematics Includes bibliographical references (leaves 137-138). This work investigates the modelling of non-stationary sample extremes using a roughness penalty approach, in which smoothed natural cubic splines are fitted to the location and scale parameters of the generalized extreme value distribution and the distribution of the r largest order statistics. Estimation is performed by implementing a Fisher scoring algorithm to maximize the penalized log-likelihood function. The approach provides a flexible framework for exploring smooth trends in sample extremes, with the benefit of balancing the trade-off between 'smoothness' and adherence to the underlying data by simply changing the smoothing parameter. To evaluate the overall performance of the extreme value theory methodology in smoothing extremes a simulation study was performed. 2014-12-27T19:45:40Z 2014-12-27T19:45:40Z 2010 Master Thesis Masters MSc http://hdl.handle.net/11427/10285 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Financial Mathematics Clur, John-Craig Nonparametric smoothing in extreme value theory |
| thesis_degree_str | Master's |
| title | Nonparametric smoothing in extreme value theory |
| title_full | Nonparametric smoothing in extreme value theory |
| title_fullStr | Nonparametric smoothing in extreme value theory |
| title_full_unstemmed | Nonparametric smoothing in extreme value theory |
| title_short | Nonparametric smoothing in extreme value theory |
| title_sort | nonparametric smoothing in extreme value theory |
| topic | Financial Mathematics |
| url | http://hdl.handle.net/11427/10285 |
| work_keys_str_mv | AT clurjohncraig nonparametricsmoothinginextremevaluetheory |