We present a new class of cluster point process models, which we call determinantal shot noise Cox processes (DSNCP), with repulsion between cluster centres. They are the special case of generalized shot noise Cox processes where the cluster centres are determinantal point processes. We establish various moment results and describe how these can be used to easily estimate unknown parameters in two particularly tractable cases, namely when the offspring density is isotropic Gaussian and the kernel of the determinantal point process of cluster centres is Gaussian or like in a scaled Ginibre point process. Through a simulation study and the analysis of a real point pattern data set we see that when modelling clustered point patterns, a much lower intensity of cluster centres may be needed in DSNCP models as compared to shot noise Cox processes.
翻译:我们提出了一个新的集束点进程模型,我们称之为定点噪音考克斯过程(DSNCP),在集聚中心之间有反作用,它们是集聚点中心是决定点过程的通用射线噪音考克斯过程的特例,我们确定各种瞬间结果,并描述如何利用这些结果来方便地估计两个特别可移动的案例中的未知参数,这两个案例中的后代密度是异向高萨,集聚中心决定点过程的内核是高西亚或类似规模大的基尼布雷过程。通过模拟研究和分析一个真正的点模式数据集,我们看到,在模拟集聚点模式时,DSNCP模型可能需要比射出的噪音考克斯过程更低的集点中心密度。