Comparer des méthodes

	Fonction K de Ripley	C de Geary (mesure globale d'autocorrélation spatiale)
Domaine	Analyse spatiale	Analyse spatiale
Famille	Hypothesis test	Hypothesis test
Année d'origine	1977	1954
Auteur d'origine	Brian Ripley	Roy C. Geary
Type	Spatial point pattern test	Global spatial autocorrelation statistic
Source fondatrice	Ripley, B. D. (1977). Modelling spatial patterns. Journal of the Royal Statistical Society: Series B, 39(2), 172–212.	Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5(3), 115–146.
Alias	Ripley's K Function, Second-Order Intensity Function, K(d) Function, Ripley K Fonksiyonu	Geary contiguity ratio, Geary's contiguity ratio, global spatial autocorrelation, Geary C mekânsal otokorelasyon
Apparentées	2	2
Résumé	The Ripley K function, introduced by Brian Ripley in 1977, is a second-order summary statistic for spatial point patterns. It measures how the number of points within a given distance d of a typical point compares to what would be expected under complete spatial randomness (CSR). Widely used in ecology, epidemiology, criminology, and geography, the K function reveals whether events cluster, disperse, or distribute randomly across a study area at multiple spatial scales simultaneously.	Geary's C is a global measure of spatial autocorrelation — whether nearby locations tend to have similar values — introduced by Roy Geary in 1954. Unlike Moran's I, which is built on the covariation of values around the mean, Geary's C is built on the squared differences between neighbouring values, making it more sensitive to local, short-range variation. Values below 1 indicate positive spatial autocorrelation (similar neighbours), near 1 indicate randomness, and above 1 indicate negative autocorrelation.