Résumé
We examine tests for the Complete Spatial Randomness (CSR) hypothesis of a point pattern in R2, based on functions of the spacing between x-ordinates and the spacing between y-ordinates. These tests extend to dimension two the one-dimensional uniformity spacings-based tests. We propose a multiple procedure based on the Rosenblatt transformation to break free from the coordinate System dependence. A real example and a simulation study show that the multiple spacings-based tests are inferior to existing tests for detecting regularity or clustering but more powerful for detecting certain types of heterogeneity, and that the multiple procedure increases the power of many other tests.