Analysis of Temporally Dependent Extremes for the Gumbel Distribution

atmire.migration.oldid1081
dc.contributor.advisorChen, Gemai
dc.contributor.advisorKim, Hyang Mi
dc.contributor.authorJi, Chaoqun
dc.date.accessioned2013-07-10T21:49:16Z
dc.date.available2013-11-12T08:00:15Z
dc.date.issued2013-07-10
dc.date.submitted2013en
dc.description.abstractFor modeling extremal behaviors, the Generalized extreme value distribution that originated from the well established Extreme Value Theory has been widely used. As a special case of such Generalized extreme value distribution, the Gumbel family is suitable for modeling maximum values from light-tailed distributions. A common assumption used in the central models of extreme values is the independence of extremes in most previous studies. However, short-term dependence among extremes might exist. In this thesis, we study a linear Gumbel distributed autoregressive model which was introduced by Toulemonde et al. (2010) to simulate dependent extremes that follow the Gumbel distribution. Our main goal is to investigate that if Gumbel distributed short-term maxima are weakly/moderately/strongly dependent, but this dependence is not recognized, what will happen to the resulting estimates of the Gumbel parameters. To reach this goal, simulations and a numerical example in environmental science are presented to quantify the above issue.en_US
dc.identifier.citationJi, C. (2013). Analysis of Temporally Dependent Extremes for the Gumbel Distribution (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/24824en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/24824
dc.identifier.urihttp://hdl.handle.net/11023/796
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectStatistics
dc.subject.classificationGumbel distributionen_US
dc.subject.classificationdependent extreme valuesen_US
dc.titleAnalysis of Temporally Dependent Extremes for the Gumbel Distribution
dc.typemaster thesis
thesis.degree.disciplineMathematics and Statistics
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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