The Disordered Chinese Restaurant and Other Competing Growth Processes

Cécile Mailler, Peter Mörters, Anna Senkevich
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Abstract

The disordered Chinese restaurant process is a partition-valued stochastic process where the elements of the partitioned set are seen as customers sitting at different tables (the sets of the partition) in a restaurant. Each table is assigned a positive number called its attractiveness. At every step a customer enters the restaurant and either joins a table with a probability proportional to the product of its attractiveness and the number of customers sitting at the table, or occupies a previously unoccupied table, which is then assigned an attractiveness drawn from a bounded distribution independently of everything else. When all attractivenesses are equal to the upper bound this process is the classical Chinese restaurant process; we show that the introduction of disorder can drastically change the behaviour of the system. Our main results are distributional limit theorems for the scaled number of customers at the busiest table, and for the ratio of occupants at the busiest and second busiest table. The limiting distributions are universal, i.e. they do not depend on the distribution of the attractiveness. They follow from two general Poisson limit theorems for a broad class of processes consisting of families growing with different rates from different birth times, which have further applications, for example to preferential attachment networks.
无序的中国餐馆和其他竞争增长过程
无序中餐馆过程是一个分区值随机过程,其中分区集的元素被视为坐在餐厅不同桌子(分区集)的顾客。每张桌子都有一个正数,叫做吸引力。在每个步骤中,顾客进入餐厅,要么以其吸引力与坐在桌子旁的顾客数量的乘积成概率加入一张桌子,要么占据一张先前未被占用的桌子,然后从一个独立于其他一切的有界分布中分配一个吸引力。当所有吸引力都等于上界时,这个过程就是古典中国餐馆的过程;我们证明了无序的引入可以极大地改变系统的行为。我们的主要结果是最繁忙的表中按比例计算的客户数量的分布极限定理,以及最繁忙表和第二繁忙表中占用者的比例。极限分布是普遍的,即它们不依赖于吸引力的分布。它们遵循两个一般泊松极限定理,适用于由不同出生时间以不同速率增长的家庭组成的大类过程,这些过程有进一步的应用,例如优先依恋网络。
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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