Kernel density estimation based on Ripley’s correction

Abstract : In this paper, we investigate a technique inspired by 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.
Complete list of metadatas

Cited literature [47 references]  Display  Hide  Download
Contributor : Anne L'Azou <>
Submitted on : Friday, December 18, 2015 - 1:39:33 PM
Last modification on : Thursday, February 7, 2019 - 5:41:00 PM
Long-term archiving on : Saturday, April 29, 2017 - 11:38:09 AM


Files produced by the author(s)



Arthur Charpentier, Ewen Gallic. Kernel density estimation based on Ripley’s correction. GeoInformatica, Springer Verlag, 2016, 20 (1), pp.95-116. ⟨10.1007/s10707-015-0232-z⟩. ⟨halshs-01238499⟩



Record views


Files downloads