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dc.contributor.advisorShort, Martin B.
dc.contributor.authorOlinde, John Garnier
dc.date.accessioned2022-05-18T19:33:55Z
dc.date.available2022-05-18T19:33:55Z
dc.date.created2022-05
dc.date.issued2022-04-28
dc.date.submittedMay 2022
dc.identifier.urihttp://hdl.handle.net/1853/66584
dc.description.abstractMany real life processes that we would like to model have a self-exciting property, i.e. the occurrence of one event causes a temporary spike in the probability of other events occurring nearby in space and time. Examples of processes that have this property are earthquakes, crime in a neighborhood, or emails within a company. In 1971, Alan Hawkes first used what is now known as the Hawkes process to model such processes. Since then much work has been done on estimating the parameters of a Hawkes process given a data set and creating variants of the process for different applications. In this thesis, we propose a new variant of a Hawkes process, called a self-limiting Hawkes process, that takes into account the effect of police activity on the underlying crime rate and an algorithm for estimating its parameters given a crime data set. We show that the self-limiting Hawkes process fits real crime data just as well, if not better, than the standard Hawkes model.We also show that the self-limiting Hawkes process fits real financial data at least as well as the standard Hawkes model.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectHawkes
dc.subjectHawkes process
dc.subjectmathematical modeling
dc.subjectself-limiting Hawkes process
dc.titleA Self-limiting Hawkes Process: Interpretation, Estimation, and Use in Modeling
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentMathematics
thesis.degree.levelDoctoral
dc.contributor.committeeMemberKang, Sung Ha
dc.contributor.committeeMemberZhou, Haomin
dc.contributor.committeeMemberLiao, Wenjing
dc.contributor.committeeMemberYan, Karen
dc.date.updated2022-05-18T19:33:55Z


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