The Burr distribution as an asymptotic law for extreme order statistics and its application to the analysis of statistical regularities in the interplanetary magnetic field

Pub Date : 2024-04-08 DOI:10.1515/rnam-2024-0006
Vladimir Bening, Victor Korolev, Natalia Sukhareva, Hong Xiaoyang, Ruslan Khaydarpashich
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Abstract

The representability of the Burr distribution as a mixture of Weibull distribution is studied in order to justify its utility for modelling the statistical regularities in extreme values registered in non-stationary flows of informative events. A result of [24] is improved by extending the domain of admissible values of the parameters which provide the representability of the (generalized) Burr distribution as a scale mixture of the Weibull distribution. This result gives an argument in favour of application of the Burr distribution as a model of statistical regularities of extreme values registered within moderate regular time intervals, say, daily (short-term) extremes. In turn, if we are interested in the statistical regularities of the behaviour of the absolute extreme observation over a long period, say, a decade (the long-term extreme), then it can be noted that the daily extreme values form a sample of the Burr-distributed random variables. As is known, the Burr distribution belongs to the domain of max-attraction of the Fréchet distribution. The problem of improving the accuracy of the approximation of the distribution of the absolute extreme by the Fréchet distribution by the construction of an asymptotic expansion for the distribution of the extreme order statistics in the sample of independent identically Burr-distributed random variables is also considered. These results are illustrated by an example of fitting the Burr distribution to the data representing the extreme values of characteristics of the interplanetary magnetic field.
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作为极阶统计渐近规律的布尔分布及其在行星际磁场统计规律性分析中的应用
研究伯尔分布作为威布尔分布混合物的可表示性,是为了证明其在模拟非稳态信息流中极端值的统计规律性方面的实用性。通过扩展参数的可容许值域,改进了 [24] 的结果,从而使(广义)布尔分布可表示为魏布勒分布的比例混合物。这一结果为应用伯尔分布作为在中等规律时间间隔内记录极端值(例如每日(短期)极端值)的统计规律模型提供了论据。反过来,如果我们感兴趣的是绝对极值在一个较长的时间段内,例如十年(长期极值)的统计规律性,那么我们可以注意到,每日极值构成了伯尔分布随机变量的一个样本。众所周知,布尔分布属于弗雷谢特分布的最大吸引域。此外,还考虑了通过构建独立同素伯尔分布随机变量样本中极值阶次统计量分布的渐近展开来提高弗雷谢特分布对绝对极值分布的近似精度的问题。将伯尔分布拟合到代表行星际磁场特征极值的数据的例子说明了这些结果。
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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