The SPP Procedure
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Overview
- Getting Started
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Syntax
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DetailsTesting for Complete Spatial RandomnessExploring Interpoint InteractionDistance Functions for Multitype Point PatternsBorder Edge Correction for Distance FunctionsConfidence Intervals for Summary StatisticsRipley-Rasson Window EstimatorCovariate Dependence TestsNonparametric Intensity EstimationInhomogeneous Poisson Process Model FittingNegative Binomial ModelingOutput Data SetsDisplayed OutputODS Table NamesODS Graphics
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Examples
- References
Ripley-Rasson Window Estimator
When the sampling window for a point pattern is unknown, it can be estimated from the data. A common error is to assume that
W is the smallest rectangle that contains the data points, or is the convex hull that encloses the data points (Baddeley 2010). Either choice is an underestimate of the true region W and usually yields an overestimate of the point process intensity 
or summary statistics such as the K function. The Ripley-Rasson window estimator is an estimate of the spatial window from
which the points were drawn (Ripley and Rasson 1977). For estimating a rectangular study region, the Ripley-Rasson estimate is the rescaled copy of the minimum bounding box
of the collection of points, centered at the box’s centroid and expanded using a scaling factor of 
, where n is the number of data points.