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Discrete Truncated Power-Law Distributions

机译:离散截断的幂律分布

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Discrete power-law distributions have significant consequences for understanding many phenomena in practice, and have attracted much attention in recent decades. However, in many practical applications, there exists a natural upper bound for the probability tail. In this paper, we develop maximum likelihood estimates for truncated discrete power-law distributions based on the upper order statistics, and large sample properties are mentioned as well. Monte Carlo simulation is carried out to examine the finite sample performance of the estimates. Applications in real cyber attack data and peak gamma-ray intensity of solar flares are highlighted.
机译:离散的幂律分布对于理解实践中的许多现象具有重要的意义,并且在最近几十年中引起了很多关注。但是,在许多实际应用中,概率尾存在自然的上限。在本文中,我们根据高阶统计量为截断的离散幂律分布开发了最大似然估计,并且还提到了较大的样本属性。进行蒙特卡洛模拟以检查估计的有限样本性能。重点介绍了在实际网络攻击数据和太阳耀斑的伽马射线峰值强度中的应用。

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