Simulation of the K-function in the analysis of spatial clustering for non-randomly distributed locations--exemplified by bovine virus diarrhoea virus (BVDV) infection in Denmark.

摘要: Abstract The K -function is often used to detect spatial clustering in point processes, e.g. of infected herds. Clustering identified by testing the observed for complete randomness modelled, a homogeneous Poisson process. approach provides information about as well scale distances clustering. However, there are several problems related applying -function, estimation size study area and assumption modelling random distribution events by, objective present was develop null hypothesis version that overcomes specific underlying characterising randomness. Furthermore, an does not include area. paper presents simulation procedure derive -function. simulated sampling N + locations from (infected ( ) non-infected N-N )). differences between empirical estimated null-hypothesis plotted together with 95% envelopes versus distance, h . In this way we test if herds differs herd general. also edge effects complex shapes region. An application bovine virus diarrhoea (BVDV) infection Denmark described.