Estimating second order characteristics of point processes with known independent noise
Estimating second order characteristics of point processes with known independent noise
复制标题
估计具有已知独立噪声的点过程的二阶特性
DOI：
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发表时间：
2012
影响因子：
2.2
通讯作者：
P. Monestiez
中科院分区：
文献类型：
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作者：
A. Bar;J. Chadoeuf;H. Dessard;P. Monestiez
点模式的分析通常从使用诸如空空间函数F或最近邻距离分布函数G之类的汇总来测试完全空间随机性开始。这些功能构成了许多研究所依据的基本摘要，这取决于它们的形状。由于点的地图通常被认为是准确的，因此在不考虑位置误差的情况下对观察到的图案进行蒙特卡罗测试。然而，在映射过程中，通常会出现位置误差。本文的目的是量化测量误差对描述性距离统计的影响，并将这些误差整合到非参数分析中。热带森林物种的应用。
The analysis of point patterns often begins with a test of complete spatial randomness using summaries such as the emptyspace function F or the nearest neighbour distance distribution function G. These functions constitute basic summaries upon which many studies are based, depending on their shape. As the map of points is usually considered accurate, Monte Carlo tests are performed on the observed pattern without taking into account position errors. However, position errors usually occur during the mapping process. The aim of this article is to quantify the impact of measurement error on descriptive distance statistics and to integrate these errors in the non-parametric analysis. An application to tropical forest species is presented.