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arXiv math/0503474math.PR
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几何概率中随机测度的高斯极限

Gaussian limits for random measures in geometric probability

Yu. Baryshnikov, J. E. Yukich

摘要:

我们建立了d维空间中由二项式和泊松点过程引起的一般测度的高斯极限。极限高斯场具有依赖于点过程密度的协方差泛函。一般结果被用来推导随机图(最近邻图、Voronoi图和影响球图)、随机序列堆积模型(弹道沉积模型和空间出生-生长模型)和统计学的胚粒模型的测度的中心极限定理。

英文摘要:

We establish Gaussian limits for general measures induced by binomial and Poisson point processes in d-dimensional space. The limiting Gaussian field has a covariance functional which depends on the density of the point process. The general results are used to deduce central limit theorems for measures induced by random graphs (nearest neighbor, Voronoi and sphere of influence graph), random sequential packing models (ballistic deposition and spatial birth-growth models) and statistics of germ-grain models.

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