Author: J. Douglas Zechar
Motivation: One of the cornerstones of science is the ability to accurately and reliably forecast natural phenomena. Unfortunately, earthquake prediction research has been plagued by controversy, and it remains an outstanding problem; for a review of some of the historical challenges, see Sue Hough's book Predicting the Unpredictable. The motivation for the work that I describe in this article is fairly self-evident: we want to know if an earthquake forecast or a set of earthquake predictions is particularly "good." Therefore, our fundamental objectives are to define and to quantify "good."
In this article, I emphasize the analysis of statements regarding future earthquake occurrence (i.e., characteristics such as origin time, epicenter, and magnitude) but many of the concepts discussed are applicable to other earthquake studies (i.e., probabilistic loss estimates, earthquake early warning, etc.). A broader motivation of this article is to encourage you to exercise rigorous hypothesis testing methods whenever the research problem allows.
Ending point: The techniques described in this article will allow you to quantify the predictive skill of an earthquake forecast or of a set of earthquake predictions. You will be able to check if an observed set of earthquakes is consistent with a forecast, and you will have some tools to compare two forecasts. Using the accompanying code and example data, you can execute each of the test methods described in this article.
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