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 in-homogeneous 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 in-homogeneous 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 non-stationary 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/student-papers/record/9042231
- author
- Steneld, Henrik LU
- supervisor
- 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
- LUNFMS-4053-2021
- ISSN
- 1654-6229
- other publication id
- 2021:K11
- language
- English
- id
- 9042231
- date added to LUP
- 2021-05-12 10:01:53
- date last changed
- 2021-06-03 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 in-homogeneous 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 non-stationary 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 = {{1654-6229}}, 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}}, }