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Kernel Density Estimation with Ripley's Circumferential Correction

Abstract : In this paper, we investigate (and extend) Ripley's circumference method to correct bias of density estimation of edges (or frontiers) of regions. The idea of the method was theoretical and difficult to implement. We provide a simple technique -- based of properties of Gaussian kernels -- to efficiently compute weights to correct border bias on frontiers of the region of interest, with an automatic selection of an optimal radius for the method. We illustrate the use of that technique to visualize hot spots of car accidents and campsite locations, as well as location of bike thefts.
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Contributor : Arthur Charpentier Connect in order to contact the contributor
Submitted on : Tuesday, October 21, 2014 - 3:52:16 PM
Last modification on : Tuesday, October 19, 2021 - 11:34:06 PM
Long-term archiving on: : Friday, April 14, 2017 - 1:32:48 PM


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  • HAL Id : hal-00725090, version 4


Arthur Charpentier, Ewen Gallic. Kernel Density Estimation with Ripley's Circumferential Correction. 2013. ⟨hal-00725090v4⟩



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