Distances and large deviations in the spatial preferential attachment model

被引:7
|
作者
Hirsch, Christian [1 ]
Moench, Christian [2 ]
机构
[1] Univ Mannheim, Inst Math, B6,26, D-68161 Mannheim, Germany
[2] Johannes Gutenberg Univ Mainz, Inst Math, Staudingerweg 9, D-55128 Mainz, Germany
关键词
distances; large deviation principle; Poisson point process; preferential attachment; NETWORKS;
D O I
10.3150/19-BEJ1121
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper considers two asymptotic properties of a spatial preferential-attachment model introduced by E. Jacob and P. Morters (In Algorithms and Models for the Web Graph (2013) 14-25 Springer). First, in a regime of strong linear reinforcement, we show that typical distances are at most of doubly-logarithmic order. Second, we derive a large deviation principle for the empirical neighbourhood structure and express the rate function as solution to an entropy minimisation problem in the space of stationary marked point processes.
引用
收藏
页码:927 / 947
页数:21
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