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Distribution of Earthquake Interevent Times in Northeast India and Adjoining Regions

机译:印度东北部及邻区的地震活动时间分布

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This study analyzes earthquake interoccurrence times of northeast India and its vicinity from eleven probability distributions, namely exponential, Frechet, gamma, generalized exponential, inverse Gaussian, Levy, lognormal, Maxwell, Pareto, Rayleigh, and Weibull distributions. Parameters of these distributions are estimated from the method of maximum likelihood estimation, and their respective asymptotic variances as well as confidence bounds are calculated using Fisher information matrices. Three model selection criteria namely the Chi-square criterion, the maximum likelihood criterion, and the Kolmogorov-Smirnov minimum distance criterion are used to compare model suitability for the present earthquake catalog (Yadav et al. in Pure Appl Geophys 167:1331-1342, 2010). It is observed that gamma, generalized exponential, and Weibull distributions provide the best fitting, while exponential, Frechet, inverse Gaussian, and lognormal distributions provide intermediate fitting, and the rest, namely Levy, Maxwell Pareto, and Rayleigh distributions fit poorly to the present data. The conditional probabilities for a future earthquake and related conditional probability curves are presented towards the end of this article.
机译:这项研究从11种概率分布分析了印度东北部及其附近地区的地震发生时间,即指数分布,弗雷谢特分布,伽马分布,广义指数分布,高斯逆分布,列维分布,对数正态分布,麦克斯韦分布,帕累托分布,瑞利分布和威布尔分布。这些分布的参数是通过最大似然估计方法估计的,并使用Fisher信息矩阵计算它们各自的渐近方差和置信范围。使用三个模型选择准则,即卡方准则,最大似然准则和Kolmogorov-Smirnov最小距离准则,比较模型对当前地震目录的适用性(Yadav等人,在Pure Appl Geophys 167:1331-1342中, 2010)。可以看出,伽玛分布,广义指数分布和威布尔分布提供了最佳拟合,而指数分布,弗雷谢特分布,高斯逆分布和对数正态分布提供了中间拟合,而其余的列维分布,麦克斯韦帕累托分布和瑞利分布与目前的拟合度很差。数据。在本文结尾处,将介绍未来地震的条件概率和相关的条件概率曲线。

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