<scp>R</scp>ipley's<scp>K</scp>Function

Abstract Ripley's K function summarizes spatial point process data. It can be used to describe a set of locations, test hypotheses about patterns, and estimate parameters in a spatial point process model. For a stationary point process, K ( t ) is the expected number of additional points within distance t of a focal point divided by the intensity of the process. A univariate version is used for one set of locations and a multivariate version is used when points can be labeled by a small number of groups. This article reviews the properties of Ripley's K function and two related functions, then illustrates the computation and interpretation using data on the locations of trees in a swamp hardwood forest.