Ornstein-Uhlenbeck processes for geophysical data analysis

In this work a three parameter stochastic process, termed the Gamma-Ornstein-Uhlenbeck process, has been implemented to analyze geophysical data. Such non-Gaussian Ornstein-Uhlenbeck processes offer the possibility of capturing important distributional deviations from Gaussianity and make the model flexible of dependence structures. It is shown that the Gamma-Ornstein-Uhlenbeck process is a possible candidate for earthquake data modeling. Rigorous regression analysis is provided and based on that the first-passage times are computed for different sets of data. It is shown that this model may be used to estimate parameters related to some major events namely major earthquakes. Published by Elsevier B.V.