Earthquake Number Forecasts Testing

Y. Kagan
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引用次数: 7

Abstract

We study the distributions of earthquake numbers in two global catalogs: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. These distributions are required to develop the number test for forecasts of future seismic activity rate. A common assumption is that the numbers are described by the Poisson distribution. In contrast to the one-parameter Poisson distribution, the negative-binomial distribution (NBD) has two parameters. The second parameter characterizes the clustering or over-dispersion of a process. We investigate the dependence of parameters for both distributions on the catalog magnitude threshold and on temporal subdivision of catalog duration. We find that for most cases of interest the Poisson distribution can be rejected statistically at a high significance level in favor of the NBD. Therefore we investigate whether these distributions fit the observed distributions of seismicity. For this purpose we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogs. A calculation of the NBD skewness and kurtosis levels shows rapid increase of these upper moments levels. However, the observed catalog values of skewness and kurtosis are rising even faster. This means that for small time intervals the earthquake number distribution is even more heavy-tailed than the NBD predicts. Therefore for small time intervals we propose using empirical number distributions appropriately smoothed for testing forecasted earthquake numbers.
地震次数预报测试
我们研究了两个全球目录中地震次数的分布:全球质心矩张量和震中的初步确定。这些分布需要发展用于预测未来地震活动率的数字检验。一个常见的假设是,这些数字是由泊松分布描述的。与单参数泊松分布不同,负二项分布有两个参数。第二个参数表示过程的聚类或过度分散。我们研究了分布参数对目录星等阈值和目录持续时间的时间细分的依赖性。我们发现,对于大多数感兴趣的情况,泊松分布可以在统计上以高显著性水平被拒绝,而有利于NBD。因此,我们研究这些分布是否符合观测到的地震活动性分布。为此,我们研究了地震数的上统计矩(偏度和峰度),并将它们与两种分布的理论值进行比较。偏度和峰度的经验值在较小的星等阈值下增加,在较小的星表时间细分下增加的强度更大。对NBD偏度和峰度水平的计算表明,这些高矩水平迅速增加。然而,观测到的偏度和峰度的目录值上升得更快。这意味着,在小的时间间隔内,地震次数的分布甚至比NBD预测的更为密集。因此,对于较小的时间间隔,我们建议使用经过适当平滑处理的经验数分布来检验预测地震次数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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