Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-27T22:18:10.712Z Has data issue: false hasContentIssue false

A non-parametric measure of spatial interaction in point patterns

Published online by Cambridge University Press:  01 July 2016

M. N. M. Van Lieshout
Affiliation:
University of Warwick
A. J. Baddeley
Affiliation:
Universities of Western Australia and Leiden

Extract

The strength and range of interpoint interactions in a spatial point process can be quantified by the function J = (1 - G)/(1 - F), where G is the nearest-neighbour distance distribution function and F the empty space function of the process. J(r) is identically equal to 1 for a Poisson process; values of J(r) smaller or larger than 1 indicate clustering or regularity, respectively. We show that, for a very large class of point processes, J(r) is constant for distances r greater than the range of spatial interaction. Hence both the range and type of interpoint interaction may be inferred from J without parametric model assumptions. We evaluate J(r) explicitly for a variety of point processes. The J function of the superposition of independent point processes is a weighted mean of the J functions of the individual processes.

Type
Stochastic Geometry and Statistical Applications
Copyright
Copyright © Applied Probability Trust 1996 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)