Iowa State University Digital Repository (Iowa State University) · 2001 · 164 citations · 0 references
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ComputingGeoinformaticsSpatial AnalysisSpatial ModelingSpatial StatisticsPoint ProcessesSpatial Data ModelsSpatial Pattern AnalysisSpatial Point ProcessesSpatial Process ModelingSpatial Statistical ModelingPoint Process EstimationRipley's K-functionRipley’s K FunctionSpatial Point Process ModelingTree Spatial PatternUnivariate Analysis
Ripley's K function sumarizes 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. A univariate version is used for one set of locations and a multivariate version is used when points can be labelled by a small number of groups. This article reviews the properties of Ripley's K function, then illustrates the computation and interpretation using data on the locations of trees in a swamp hardwood forest.