Normal Approximation in Geometric Probability
Probability
2007-05-23 v1
Abstract
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.
Cite
@article{arxiv.math/0409088,
title = {Normal Approximation in Geometric Probability},
author = {Mathew D. Penrose and J. E. Yukich},
journal= {arXiv preprint arXiv:math/0409088},
year = {2007}
}
Comments
To appear in the proceedings of the Workshop on Stein's Method and Applications, 11-15 August 2003, Institute of Mathematical Sciences, National University of Singapore