Nonparametric smoothing in extreme value theory

 

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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


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