An extreme value approach to modelling number of causalities in earthquakes
(2021) In Bachelor's Theses in Mathematical Sciences MASK11 20201Mathematical Statistics
 Abstract
 Earthquakes occur around the globe all the time. Most are weak enough to just pass by, some are strong enough to be felt by us humans, and some very few are completely devastating. A comprehensive database distributed by NOAA National Centers for Environmental Information provides a means for reviewing devastating earthquakes over the past. Extreme value theory has previously been applied to modelling earthquakes, although for the most part the modelling has been concerned with the magnitudes. In this thesis, extreme value theory has been applied to the number of casualties that are directly or indirectly the result of an earthquake.
An inhomogeneous Poisson point process is fitted to events where the death toll is at least ten or... (More)  Earthquakes occur around the globe all the time. Most are weak enough to just pass by, some are strong enough to be felt by us humans, and some very few are completely devastating. A comprehensive database distributed by NOAA National Centers for Environmental Information provides a means for reviewing devastating earthquakes over the past. Extreme value theory has previously been applied to modelling earthquakes, although for the most part the modelling has been concerned with the magnitudes. In this thesis, extreme value theory has been applied to the number of casualties that are directly or indirectly the result of an earthquake.
An inhomogeneous Poisson point process is fitted to events where the death toll is at least ten or more. The events are assumed to be independent but nonstationary with respect to the magnitude of the earthquake. This leads to a Poisson point process with an intensity which is a function of magnitude. In addition, an assumption is made about the distribution of the magnitudes of earthquakes, which provides the necessary means for modelling extremes of earthquakes death toll unconditional of magnitude. With the aid of simulations and the asymptotic normality of maximum likelihood estimators, return levels and corresponding confidence intervals are calculated for three different geographical regions. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/9042231
 author
 Steneld, Henrik ^{LU}
 supervisor

 Nader Tajvidi ^{LU}
 organization
 course
 MASK11 20201
 year
 2021
 type
 M2  Bachelor Degree
 subject
 keywords
 Extreme Value Theory, Point Process, Earthquakes
 publication/series
 Bachelor's Theses in Mathematical Sciences
 report number
 LUNFMS40532021
 ISSN
 16546229
 other publication id
 2021:K11
 language
 English
 id
 9042231
 date added to LUP
 20210512 10:01:53
 date last changed
 20210603 15:08:52
@misc{9042231, abstract = {{Earthquakes occur around the globe all the time. Most are weak enough to just pass by, some are strong enough to be felt by us humans, and some very few are completely devastating. A comprehensive database distributed by NOAA National Centers for Environmental Information provides a means for reviewing devastating earthquakes over the past. Extreme value theory has previously been applied to modelling earthquakes, although for the most part the modelling has been concerned with the magnitudes. In this thesis, extreme value theory has been applied to the number of casualties that are directly or indirectly the result of an earthquake. An inhomogeneous Poisson point process is fitted to events where the death toll is at least ten or more. The events are assumed to be independent but nonstationary with respect to the magnitude of the earthquake. This leads to a Poisson point process with an intensity which is a function of magnitude. In addition, an assumption is made about the distribution of the magnitudes of earthquakes, which provides the necessary means for modelling extremes of earthquakes death toll unconditional of magnitude. With the aid of simulations and the asymptotic normality of maximum likelihood estimators, return levels and corresponding confidence intervals are calculated for three different geographical regions.}}, author = {{Steneld, Henrik}}, issn = {{16546229}}, language = {{eng}}, note = {{Student Paper}}, series = {{Bachelor's Theses in Mathematical Sciences}}, title = {{An extreme value approach to modelling number of causalities in earthquakes}}, year = {{2021}}, }