JavaScript is disabled for your browser. Some features of this site may not work without it.
- OpenUCT Home
- →
- Theses / Dissertations
- →
- Masters
- →
- View Item
| dc.contributor.advisor | Haines, Linda | en_ZA |
| dc.contributor.author |
Clur, John-Craig
|
en_ZA |
| dc.date.accessioned | 2014-12-27T19:45:40Z | |
| dc.date.available | 2014-12-27T19:45:40Z | |
| dc.date.issued | 2010 | en_ZA |
| dc.identifier.citation | Clur, J. 2010. Nonparametric smoothing in extreme value theory. University of Cape Town. | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/10285 | |
| dc.description | Includes bibliographical references (leaves 137-138). | en_ZA |
| dc.description.abstract | 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. | en_ZA |
| dc.language.iso | eng | en_ZA |
| dc.subject.other | Financial Mathematics | en_ZA |
| dc.title | Nonparametric smoothing in extreme value theory | en_ZA |
| dc.type | Master Thesis | |
| uct.type.publication | Research | en_ZA |
| uct.type.resource | Thesis | en_ZA |
| dc.publisher.institution | University of Cape Town | |
| dc.publisher.faculty | Faculty of Science | en_ZA |
| dc.publisher.department | Department of Statistical Sciences | en_ZA |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MSc | en_ZA |
| uct.type.filetype | Text | |
| uct.type.filetype | Image | |
| dc.identifier.apacitation | Clur, J. (2010). <i>Nonparametric smoothing in extreme value theory</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/10285 | en_ZA |
| dc.identifier.chicagocitation | Clur, John-Craig. <i>"Nonparametric smoothing in extreme value theory."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2010. http://hdl.handle.net/11427/10285 | en_ZA |
| dc.identifier.vancouvercitation | Clur J. Nonparametric smoothing in extreme value theory. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2010 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/10285 | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Clur, John-Craig AB - 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. DA - 2010 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2010 T1 - Nonparametric smoothing in extreme value theory TI - Nonparametric smoothing in extreme value theory UR - http://hdl.handle.net/11427/10285 ER - | en_ZA |
