Date of Award

2019-01-01

Degree Name

Master of Science

Department

Mathematical Sciences

Advisor(s)

Maria C. Mariani

Abstract

With about 226050 estimated deaths worldwide in 2010, earthquake is considered as one of the disasters that record a great number of deaths. This Thesis develops a model for the estimation of magnitude of future seismic events.

We propose a stochastic differential equation arising on the Ornstein-Uhlenbeck processes driven by Inverse Gaussian (a,b) process. Inverse Gaussian (a,b) Ornstein-Uhlenbeck processes offer analytic flexibility and provides a class of continuous time processes capable of exhibiting long memory behavior. The stochastic differential equation is applied to geophysics and financial stock market by fitting the superposed Inverse Gaussian (a,b) Ornstein-Uhlenbeck model to earthquake and financial time series.

Language

en

Provenance

Received from ProQuest

File Size

69 pages

File Format

application/pdf

Rights Holder

Emmanuel Kofi Kusi

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