arXiv Analytics

Sign in

arXiv:math/0409088 [math.PR]AbstractReferencesReviewsResources

Normal Approximation in Geometric Probability

Mathew D. Penrose, J. E. Yukich

Published 2004-09-06Version 1

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.

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
Categories: math.PR
Subjects: 60D05, 60F05
Related articles: Most relevant | Search more
arXiv:2011.07781 [math.PR] (Published 2020-11-16)
Normal approximation in total variation for statistics in geometric probability
arXiv:1409.6380 [math.PR] (Published 2014-09-23)
Normal approximation of Gibbsian sums in geometric probability
arXiv:math/0107149 [math.PR] (Published 2001-07-20)
Weak Laws in Geometric Probability