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Asymptotic normality determined by high moments, and submap counts of random maps

机译:高矩确定的渐近正态性,以及随机图的子图计数

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摘要

We give a general result showing that the asymptotic behaviour of high moments determines the shape of distributions which are asymptotically normal. Both the factorial and non-factorial (non-central) moments are treated. This differs from the usual moment method in combinatorics, as the expected value may tend to infinity quite rapidly. Applications are given to submap counts in random planar triangulations, where we use a simple argument to asymptotically determine high moments for the number of copies of a given subtriangulation in a random 3-connected planar triangulation. Similar results are also obtained for 2-connected triangulations and quadrangulations with no multiple edges.
机译:我们给出的一般结果表明,高矩的渐近行为决定了渐近正态分布的形状。阶乘和非阶乘(非中心)矩均被处理。这与组合法中通常的矩量法不同,因为期望值可能会非常迅速地趋于无穷大。随机平面三角剖分中的子图计数得到了应用,其中我们使用一个简单的参数来渐近确定随机三连接平面三角剖分中给定子三角剖分副本数的高矩。对于没有多个边的2连接的三角剖分和四角剖分,也获得了相似的结果。

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