Local weak limits for collapsed branching processes with random out-degrees

IF 1.1 2区 数学 Q3 STATISTICS & PROBABILITY
Sayan Banerjee, Prabhanka Deka, Mariana Olvera-Cravioto
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引用次数: 0

Abstract

We obtain local weak limits in probability for Collapsed Branching Processes (CBP), which are directed random networks obtained by collapsing random-sized families of individuals in a general continuous-time branching process. The local weak limit of a given CBP, as the network grows, is shown to be a related continuous-time branching process stopped at an independent exponential time. The proof involves the construction of an explicit coupling of the in-components of vertices with the limiting object. We also show that the in-components of a finite collection of uniformly chosen vertices locally weakly converge (in probability) to i.i.d. copies of the above limit, reminiscent of propagation of chaos in interacting particle systems. We obtain as special cases novel descriptions of the local weak limits of directed preferential and uniform attachment models. We also outline some applications of our results for analyzing the limiting in-degree and PageRank distributions. In particular, upper and lower bounds on the tail of the in-degree distribution are obtained and a phase transition is detected in terms of the growth rate of the attachment function governing reproduction rates in the branching process.
具有随机出度的可折叠分支过程的局部弱极限
本文给出了在一般连续时间分支过程中,由随机大小的个体族坍缩而得到的有向随机网络的局部弱概率极限。给定CBP的局部弱极限,随着网络的增长,被证明是一个相关的连续分支过程,停止于一个独立的指数时间。证明涉及顶点的内分量与极限对象的显式耦合的构造。我们还证明了一致选择顶点的有限集合的内分量局部弱收敛(在概率上)到上述极限的i.d个副本,使人想起相互作用粒子系统中的混沌传播。作为特例,我们得到了定向优先和一致依恋模型的局部弱极限的新描述。我们还概述了我们的结果在分析限制度和PageRank分布方面的一些应用。特别地,得到了在度分布尾部的上界和下界,并根据分支过程中控制繁殖率的附着函数的增长率检测到相变。
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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来源期刊
Stochastic Processes and their Applications
Stochastic Processes and their Applications 数学-统计学与概率论
CiteScore
2.90
自引率
7.10%
发文量
180
审稿时长
23.6 weeks
期刊介绍: Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.
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