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Normal Approximation in Geometric Probability by Penrose, Mathew D.; Yukich, J. E. is a scholarly article available to read on EtoBox.

What is Normal Approximation in Geometric Probability about?

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.

Author

Penrose, Mathew D.; Yukich, J. E.

Published

2004

Language

EN