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Application of hidden Markov and related models to earthquake studies

dc.contributor.degreegrantinginstitutionAthens University of Economics and Business, Department of Statisticsel
dc.contributor.thesisadvisorKarlis, Dimitriosel
dc.creatorOrfanogiannaki, Aikaterini M.en
dc.creatorΟρφανογιαννάκη, Αικατερίνη Μ.el
dc.date.accessioned2025-03-26T19:45:15Z
dc.date.available2025-03-26T19:45:15Z
dc.date.issued2015
dc.description.abstractDiscrete valued hidden Markov Models (HMMs) are used to model time series of event counts in several scientific fields like genetics, engineering, seismology and finance. In its general form the model consists of two parts: the observation sequence and an unobserved sequence of hidden states that underlies the data and consist a Markov chain. Each state is characterized by a specific distribution and the progress of the hidden process from state to state is controlled by a transition probability matrix. We extend the theory of HMMs to the multivariate case and apply them to seismological data fromdifferent seismotectonic environments. This extension is not straightforward and it is achieved gradually by assuming different multivariate distributions to describe each state of the model.el
dc.format.extent182p.
dc.identifier.urihttps://pyxida.aueb.gr/handle/123456789/7532
dc.languageen
dc.rightsCC BY: Attribution alone 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectHidden Markov Models (HMMs)el
dc.subjectSeismologyel
dc.subjectEM algorithmel
dc.titleApplication of hidden Markov and related models to earthquake studiesen
dc.title.alternativeΕφαρμογή των λανθανόντων μοντέλων Markov και σχετικών μοντέλων σε μελέτες σεισμώνel
dc.typeText

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