Generalizing Ripley's K Function to Inhomogeneous Populations

1 We wish to thank Gabriel Lang for his helpful comments. 2 Corresponding author, AgroParisTech ENGREF, UMR EcoFoG, BP 316, 97310 Kourou, French Guyana. E-Mail: [email protected] 3 LET (Université de Lyon, CNRS, ENTPE), Institut des Sciences de l’Homme, 14 av. Berthelot, 69363 Lyon Cedex 07, France. E-Mail: [email protected] Abstract: In spatial statistics, Ripley’s K function (Ripley (1977)) is a classical tool to analyse spatial point patterns. Yet, it faces two major limits: it is only pertinent for homogeneous point processes and it does not allow the weighting of points. We generalize it to get a new function, M, which oversteps these limits and detects spatial structures of inhomogeneous populations of weighted points.