POINT-BASED POLYGONAL MODELS FOR RANDOM GRAPHS

被引：26
|
作者：
ARAK, T
CLIFFORD, P
SURGAILIS, D
机构：
[1] UNIV OXFORD,DEPT STAT,OXFORD OX1 3TG,ENGLAND
[2] VILNIUS MATH & INFORMAT INST,VILNIUS 232600,LITHUANIA
来源：
ADVANCES IN APPLIED PROBABILITY | 1993年 / 25卷 / 02期
关键词：
MARKOV GRAPHS; CONSISTENT MODELS; PARTICLE SYSTEMS; POISSON SEGMENT PROCESS; POLYMERIZATION;
D O I：
10.2307/1427657
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：
We define a class of two-dimensional Markov random graphs with I, V, T and Y-shaped nodes (vertices). These are termed polygonal models. The construction extends our earlier work [1]-[5]. Most of the paper is concerned with consistent polygonal models which are both stationary and isotropic and which admit an alternative description in terms of the trajectories in space and time of a one-dimensional particle system with motion, birth, death and branching. Examples of computer simulations based on this description are given.
引用
收藏
页码：348 / 372
页数：25
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