Assessment of Point Process Models for Earthquake Forecasting
Abstract
Models for forecasting earthquakes are currently tested prospectively in well-organized testing centers, using data collected after the models and their parameters are completely specified. The extent to which these models agree with the data is typically assessed using a variety of numerical tests, which unfortunately have low power and may be misleading for model comparison purposes. Promising alternatives exist, especially residual methods such as super-thinning and Voronoi residuals. This article reviews some of these tests and residual methods for determining the goodness of fit of earthquake forecasting models.
Cite
@article{arxiv.1312.5934,
title = {Assessment of Point Process Models for Earthquake Forecasting},
author = {Andrew Bray and Frederic Paik Schoenberg},
journal= {arXiv preprint arXiv:1312.5934},
year = {2013}
}
Comments
Published in at http://dx.doi.org/10.1214/13-STS440 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)