On tests of spatial pattern based on simulation envelopes
On tests of spatial pattern based on simulation envelopes
复制标题
DOI：
10.1890/13-2042.1
复制
发表时间：
2014-08-01
影响因子：
6.1
通讯作者：
Nair, Gopalan
中科院分区：
文献类型：
--
作者：
Baddeley, Adrian;Diggle, Peter J.;Nair, Gopalan
在空间点型分析中，基于模拟包络的统计检验起着重要的作用，如Ripley’s K函数的模拟包络。最近的生态学文献正确地指出了模拟包络解释中的一个常见错误。然而，这导致了一种普遍的信念，即测试本身是无效的。相反，在适当的条件下，基于包络的统计检验是正确的统计程序。在本文中，我们解释了蒙特卡罗测试的原理及其正确解释，概述了图形化程序的好处，测量了几种流行测试的统计性能，并提出了实用的建议。有几个注意事项，包括未被认识到的问题，即如果必须从数据中估计模型参数，蒙特卡罗拟合优度测试可能是保守的。最后，我们讨论了模拟包络图是否可以用来推断空间相互作用的尺度。
In the analysis of spatial point patterns, an important role is played by statistical tests based on simulation envelopes, such as the envelope of simulations of Ripley's K function. Recent ecological literature has correctly pointed out a common error in the interpretation of simulation envelopes. However, this has led to a widespread belief that the tests themselves are invalid. On the contrary, envelope-based statistical tests are correct statistical procedures, under appropriate conditions. In this paper, we explain the principles of Monte Carlo tests and their correct interpretation, canvas the benefits of graphical procedures, measure the statistical performance of several popular tests, and make practical recommendations. There are several caveats including the under-recognized problem that Monte Carlo tests of goodness of fit are probably conservative if the model parameters have to be estimated from data. Finally, we discuss whether graphs of simulation envelopes can be used to infer the scale of spatial interaction.