Abstract
Analysis of data in the form of a set of points irregularly distributed within a region of space usually involves the study of some property of the distribution of inter-event distances. One such function is G, the distribution of the distance from an event to its nearest neighbor. In practice, point processes are commonly observed through a bounded window, thus making edge effects an important component in the estimation of G. Several estimators have been proposed, all dealing with the edge effect problem in different ways. This paper proposes a new alternative for estimating the nearest neighbor distribution and compares it to other estimators. The result is an estimator with relatively small mean squared error for a wide variety of stationary processes.
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