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A Remark on the Van Lieshout and Baddeley J-Function for Point Processes

Published online by Cambridge University Press:  01 July 2016

T. Bedford*
Affiliation:
Delft University of Technology
J. Van Den Berg*
Affiliation:
CWI
*
Postal address: Delft University of Technology, Faculty of Technical Mathematics and Informatics, Mekelweg 4, 2628 CD Delft, The Netherlands.
∗∗ Postal address: CWI, Kruislaan 413, 1098 SJ Amsterdam, The Netherlands.

Abstract

The empty space function of a stationary point process in ℝd is the function that assigns to each r, r > 0, the probability that there is no point within distance r of O. In a recent paper Van Lieshout and Baddeley study the so-called J-function, which is defined as the ratio of the empty space function of a stationary point process and that of its corresponding reduced Palm process. They advocate the use of the J-function as a characterization of the type of spatial interaction.

Therefore it is natural to ask whether J ≡ 1 implies that the point process is Poisson. We restrict our analysis to the one-dimensional case and show that a classical construction by Szász provides an immediate counterexample. In this example the interpoint distances are still exponentially distributed. This raises the question whether it is possible to have J ≡ 1 but non-exponentially distributed interpoint distances. We construct a point process with J ≡ 1 but where the interpoint distances are bounded.

Type
Stochastic Geometry and Statistical Applications
Copyright
Copyright © Applied Probability Trust 1997 

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References

Bedford, T. and Meilijson, I. (1993) A characterisation of marginal distributions of (possibly dependent) lifetime variables which right censor each other. Report 93-116. TU Delft.Google Scholar
Daley, D. J. and Vere-Jones, D. (1988) An Introduction to the Theory of Point Processes. Springer, New York.Google Scholar
Van Lieshout, M. N. M. and Baddeley, A. (1996) A nonparametric measure of spatial interaction in point patterns. Statist. Neerlandica. 50, 344361.CrossRefGoogle Scholar
Stoyan, D., Kendall, W. S. and Mecke, J. (1995) Stochastic Geometry and its Applications. 2nd edn. Wiley, New York.Google Scholar
SzÁSz, D. (1970) Once more on the Poisson process. Studia Sci. Math. Hungarica 5, 441444.Google Scholar