Department of Mathematics
A goodness‐of‐fit test statistic for spatial point processes is proposed and shown to have an asymptotic chi‐squared distribution if the underlying point process is Poisson. Simulations demonstrate that the test, when testing for complete spatial randomness, is more sensitive to mixtures of regular and clustered point processes than the tests using the nearest neighbour distance distribution, the second‐ or third‐order characteristics/
Clustered point pattern, Forest stand, Goodness of fit, Poisson process, Regular point pattern
Source Publication Title
Oxford University Press
This is a pre-copyedited, author-produced version of an article accepted for publication in Biometrika following peer review. The version of record P. Grabarnik, S. N. Chiu; Goodness‐of‐fit test for complete spatial randomness against mixtures of regular and clustered spatial point processes. Biometrika 2002; 89 (2): 411-421. doi: 10.1093/biomet/89.2.411 is available online at: https://doi.org/10.1093/biomet/89.2.411.
This research was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China, and a Faculty Research Grant of the Hong Kong Baptist University.
Link to Publisher's Edition
Grabarnik, P., & Chiu, S. (2002). Goodness‐of‐fit test for complete spatial randomness against mixtures of regular and clustered spatial point processes. Biometrika, 89 (2), 411-421. https://doi.org/10.1093/biomet/89.2.411