The longest edge in discrete and continuous long-range percolation

IF 1.1 3区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Extremes Pub Date : 2024-06-18 DOI:10.1007/s10687-024-00488-y
Arnaud Rousselle, Ercan Sönmez
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Abstract

We consider the random connection model in which an edge between two Poisson points at distance r is present with probability g(r). We conduct an extreme value analysis on this model, namely by investigating the longest edge with at least one endpoint within some finite observation window, as the volume of this window tends to infinity. We show that the length of the latter, after normalizing by some appropriate centering and scaling sequences, asymptotically behaves like one of each of the three extreme value distributions, depending on choices of the probability g(r). We prove our results by giving a formal construction of the model by means of a marked Poisson point process and a Poisson coupling argument adapted to this construction. In addition, we study a discrete variant of the model. We obtain parameter regimes with varying behavior in our findings and an unexpected singularity.

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离散和连续长程渗流中的最长边缘
我们考虑了随机连接模型,在该模型中,距离为 r 的两个泊松点之间存在一条边的概率为 g(r)。我们对这一模型进行了极值分析,即研究在某个有限观测窗口内至少有一个端点的最长边,当窗口的容积趋于无穷大时。我们证明,后者的长度在通过一些适当的居中和缩放序列进行归一化后,渐近地表现为三种极值分布中的一种,这取决于概率 g(r) 的选择。我们通过有标记的泊松点过程给出了模型的正式构造,并给出了与此构造相适应的泊松耦合论证,从而证明了我们的结果。此外,我们还研究了该模型的离散变体。我们在研究结果中获得了行为各异的参数区以及一个意想不到的奇点。
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来源期刊
Extremes
Extremes MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.20
自引率
7.70%
发文量
15
审稿时长
>12 weeks
期刊介绍: Extremes publishes original research on all aspects of statistical extreme value theory and its applications in science, engineering, economics and other fields. Authoritative and timely reviews of theoretical advances and of extreme value methods and problems in important applied areas, including detailed case studies, are welcome and will be a regular feature. All papers are refereed. Publication will be swift: in particular electronic submission and correspondence is encouraged. Statistical extreme value methods encompass a very wide range of problems: Extreme waves, rainfall, and floods are of basic importance in oceanography and hydrology, as are high windspeeds and extreme temperatures in meteorology and catastrophic claims in insurance. The waveforms and extremes of random loads determine lifelengths in structural safety, corrosion and metal fatigue.
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