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arXiv math/0409088math.PR
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几何概率中的正态逼近

Normal Approximation in Geometric Probability

Mathew D. Penrose, J. E. Yukich

摘要:

我们使用Stein的方法来获得收敛速率上的界的一类统计量的几何概率作为一个总和的贡献泊松点是指数稳定的,即局部确定在一定意义上。例子包括统计,如总边长和计算几何图形的总边数和随机序列包装模型中接受的粒子总数。这些速率也适用于与这些统计量相关的随机测量的1维边缘。

英文摘要:

We use Stein's method to obtain bounds on the rate of convergence for a class of statistics in geometric probability obtained as a sum of contributions from Poisson points which are exponentially stabilizing, i.e. locally determined in a certain sense. Examples include statistics such as total edge length and total number of edges of graphs in computational geometry and the total number of particles accepted in random sequential packing models. These rates also apply to the 1-dimensional marginals of the random measures associated with these statistics.

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