Nonparametric estimation of the dependence of a spatial point process on spatial covariates
Nonparametric estimation of the dependence of a spatial point process on spatial covariates
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DOI：
10.4310/sii.2012.v5.n2.a7
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发表时间：
2012
影响因子：
0.8
通讯作者：
A. Baddeley;Ya-Mei Chang;Yong Song;Rolf Turner
中科院分区：
文献类型：
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作者：
A. Baddeley;Ya-Mei Chang;Yong Song;Rolf Turner
在空间点格局的统计分析中，研究点格局是否依赖于空间协变量是非常重要的。本文描述了估计空间协变量对点过程强度影响的非参数（核似然和局部似然）方法。方差估计和置信区间提供在泊松点过程的情况下。通过模拟实例以及在地质和森林生态勘探中的应用，对技术进行了论证。
In the statistical analysis of spatial point patterns, it is often important to investigate whether the point pattern depends on spatial covariates. This paper describes nonparametric (kernel and local likelihood) methods for estimating the effect of spatial covariates on the point process intensity. Variance estimates and confidence intervals are provided in the case of a Poisson point process. Techniques are demonstrated with simulated examples and with applications to exploration geology and forest ecology.