STATISTICAL INFERENCE METHODS FOR SPATIAL POINT PATTERN OF WHITE-CAP BREAKING
CHEN Jia;LEI Shu-He;GUAN Chang-Long;ZHANG Chong;TAO Shan-Shan;The College of Mathematics,Ocean University of China;The Laboratory of Physical Oceanography,Ocean University of China;The College of Engineering,Ocean University of China;
For a long time, research on white-cap breaking does not involve the issue of spatial distribution pattern. However, the spatial distribution pattern is the premise of research for describing the statistical characteristic of breaking waves. By applying the theory of spatial point process with statistical inference tools, we studied white-cap breaking and modeled its spatial distribution. Combining with the real white-cap breaking images, we calculated the L-function and the K-function of the observed patterns, and used MCMC(Markov chain Monte Carlo) random simulation test against the null hypothesis about homogeneous Poisson process, making the K-function as basic statistics for inferring that the spatial point pattern of the observed images we chose is homogeneous Poisson process. Case studies show that the statistical tools of spatial point process can be applied effectively for research on white-cap breaking.