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.
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页码:927 / 947
页数:21
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