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.
Liste complète des métadonnées

Cited literature [47 references]  Display  Hide  Download

https://halshs.archives-ouvertes.fr/halshs-01238499
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
Document(s) archivé(s) le : Saturday, April 29, 2017 - 11:38:09 AM

File

Charpentier-Gallic-ripley-2015...
Files produced by the author(s)

Identifiers

Citation

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⟩

Share

Metrics

Record views

731

Files downloads

464