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dc.contributor.advisorNæss, Arvidnb_NO
dc.contributor.authorHaug, Evennb_NO
dc.date.accessioned2014-12-19T13:57:59Z
dc.date.available2014-12-19T13:57:59Z
dc.date.created2010-09-04nb_NO
dc.date.issued2008nb_NO
dc.identifier348653nb_NO
dc.identifierntnudaim:4119nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/258439
dc.description.abstractThe thesis describes the Average Exceedance Rate (AER) method, which is a method for predicting return levels from sampled time series. The AER method is an alternative to the Peaks over threshold (POT) method, which is based on the assumption that data exceeding a certain threshold will behave asymptotically. The AER methods avoids this assumption by using sub-asymptotic data instead. Also, instead of using declustering to obtain independent data, correlation among the data is dealt with by assuming a Markov-like property. A practical procedure for using the AER method is proposed and tested on two sets of real data. These are a set of wind speed data from Norway and a set of wave height data from the Norwegian continental shelf. From the results, the method appears to give satisfactory results for the wind speed data, but for the wave height data its use appears to be invalid. However, the method itself seems to be robust, and to have certain advantages when compared to the POT method.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for matematiske fagnb_NO
dc.subjectntnudaimno_NO
dc.subjectSIF3 fysikk og matematikkno_NO
dc.subjectIndustriell matematikkno_NO
dc.titleMethods for Extreme Value Statistics Based on Measured Time Seriesnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber72nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for matematiske fagnb_NO


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