Spatial Point Processes and their Applications
Spatial Point Processes and their Applications
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DOI：
10.1007/978-3-540-38175-4_1
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发表时间：
2007
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影响因子：
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通讯作者：
W. Weil
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文献类型：
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作者：
W. Weil
空间点过程是d维空间（通常在应用中d= 2或d= 3）中点的随机模式。空间点过程在分析观测到的点的模式时作为统计模型是有用的，其中点代表一些研究对象的位置（例如……）（森林中的树木、鸟巢、疾病病例或轻微犯罪）。点过程在随机几何中扮演着特殊的角色，作为更复杂的随机集模型（如布尔模型）的构建块，以及作为随机集的指导简单示例。这些讲座介绍空间点过程的基本概念，着眼于应用，并以最少的技术细节。它们涵盖了构造、操作和分析空间点过程的方法，以及分析空间点模式数据的方法。每堂课都以一套实用的计算机练习结束，读者可以通过下载一个免费软件包来完成这些练习。
A spatial point process is a random pattern of points in d-dimensional space (where usually d= 2 or d= 3 in applications). Spatial point processes are useful as statistical models in the analysis of observed patterns of points, where the points represent the locations of some object of study (e.. g. trees in a forest, bird nests, disease cases, or petty crimes). Point processes play a special role in stochastic geometry, as the building blocks of more complicated random set models (such as the Boolean model), and as instructive simple examples of random sets.These lectures introduce basic concepts of spatial point processes, with a view toward applications, and with a minimum of technical detail. They cover methods for constructing, manipulating and analysing spatial point processes, and for analysing spatial point pattern data. Each lecture ends with a set of practical computer exercises, which the reader can carry out by downloading a free software package.