Optimal discretization for geographical detectors-based risk assessment
Optimal discretization for geographical detectors-based risk assessment
复制标题
基于地理探测器的风险评估的最佳离散化
DOI：
10.1080/15481603.2013.778562
复制
发表时间：
2013-01-01
影响因子：
6.7
通讯作者：
Wang, Jin-Feng
中科院分区：
文献类型：
--
作者：
Cao, Feng;Ge, Yong;Wang, Jin-Feng
地理检测器模型是一种新的健康风险空间分析方法。它适用于离散的风险因素。同时，地理检测器模型通过将连续数据离散化为离散数据，有效地分析了连续风险因素。最大的困难是决定如何使用最合适的离散化方法来离散连续的风险因素。在本文中，我们将讨论一个最佳的离散化方法的选择，地理探测器为基础的风险评估，并使用神经管缺陷（NTD）从中国山西省和顺县，中国的过程。
The geographical detectors model is a new spatial analysis method for the assessment of health risks. It is adapted to discrete risk factors. Meanwhile, the geographical detectors model also effectively analyzes the continuous risk factors by discretizing the continuous data into discrete data. The biggest difficulty is in deciding how to discretize continuous risk factors using the most appropriate discretization method. In this paper, we will discuss the selection of an optimal discretization method for geographical detectors-based risk assessment, and exemplify the process using neural tube defects (NTD) from the Heshun County, Shanxi Province, China.