Master of Science in Mathematical Science
First Committee Member
Chih-Hsiang Ho, Chair
Second Committee Member
Third Committee Member
Graduate Faculty Representative
Number of Pages
Earthquakes that occurred worldwide during the period of 1896 to 2009 with magnitude greater than or equal to 8.0 on the Richter scale are assumed to follow a Poisson process. Autoregressive Integrated Moving Average models are presented to fit the empirical recurrence rates, and to predict future large earthquakes. We show valuable modeling and computational techniques for the point processes and time series data. Specifically, for the proposed methodology, we address the following areas: data management and graphic presentation, model fitting and selection, model validation, model and data sensitivity analysis, and forecasting.
Autoregressive Integrated Moving Average (ARIMA); Earthquake prediction; Poisson processes
Applied Statistics | Geophysics and Seismology | Mathematics | Statistics and Probability
University of Nevada, Las Vegas
Fu, Wangdong, "ARIMA model for forecasting Poisson data: Application to long-term earthquake predictions" (2010). UNLV Theses, Dissertations, Professional Papers, and Capstones. 897.
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