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A new metric between distributions of point processes

Published online by Cambridge University Press:  01 July 2016

Dominic Schuhmacher*
Affiliation:
The University of Western Australia
Aihua Xia*
Affiliation:
The University of Melbourne
*
Current address: Institute of Mathematical Statistics and Actuarial Science, University of Bern, Alpeneggstrasse 22, CH-3012 Bern, Switzerland. Email address: [email protected]
∗∗ Postal address: Department of Mathematics and Statistics, The University of Melbourne, Parkville, VIC 3010, Australia. Email address: [email protected]
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Abstract

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Most metrics between finite point measures currently used in the literature have the flaw that they do not treat differing total masses in an adequate manner for applications. This paper introduces a new metric 1 that combines positional differences of points under a closest match with the relative difference in total mass in a way that fixes this flaw. A comprehensive collection of theoretical results about 1 and its induced Wasserstein metric 2 for point process distributions are given, including examples of useful 1-Lipschitz continuous functions, 2 upper bounds for the Poisson process approximation, and 2 upper and lower bounds between distributions of point processes of independent and identically distributed points. Furthermore, we present a statistical test for multiple point pattern data that demonstrates the potential of 1 in applications.

Type
Stochastic Geometry and Statistical Applications
Copyright
Copyright © Applied Probability Trust 2008 

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