On Spatial Point Processes With Composition‐Valued Marks
针对成分值标记（向量值且和为常数）的空间点过程，扩展了现有方法并调整了常用标记特征，应用于树木冠基比和商业部门构成的空间相关性分析。
Summary Methods for marked spatial point processes with scalar marks have seen extensive development in recent years. While the impressive progress in data collection and storage capacities has yielded an immense increase in spatial point process data with highly challenging non‐scalar marks, methods for their analysis are not equally well developed. In particular, there are no methods for composition‐valued marks, that is, vector‐valued marks with a sum‐to‐constant constrain (typically 1 or 100). Prompted by the need for a suitable methodological framework, we extend existing methods to spatial point processes with composition‐valued marks and adapt common mark characteristics to this context. The proposed methods are applied to analyse spatial correlations in data on tree crown‐to‐base and business sector compositions.