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Deakin University, School of Information technology, Geelong, Victoria, 3217, Australia

机译:Deakin University,信息技术学院,吉朗,维多利亚,3217,澳大利亚

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This paper presents the application of Exploratory Spatial Data Analysis (ESDA) and Kriging from GIS (ArcGIS8.3) in disease mapping through the analysis of hepatitis B in China. The research shows that geostatistical analysis techniques such as Kriging and ESDA have a good effect in disease mapping. Kriging methods can express properly the spatial correlation. Furthermore, unlike model-based methods, which largely depend on assumption for disease data, the Kriging method is more robust for the data. So it can be used more widely and is more operational. Whats more, the Kriging method may be adapted to interpolate nonstationary spatial structure. This can expand its application more largely. At last, the Kriging method can estimate the uncertainty of prediction while many deterministic methods cannot do so. In conclusion, it is an effective operational procedure to gain a deep insight into the disease data through ESDA before mapping disease using the Kriging method.
机译:本文介绍了探索性空间数据分析(ESDA)和Kriging通过中国乙型肝炎的分析来实现GIS(ArcGIS8.3)的疾病映射。该研究表明,克里格汀和ESDA等地统计分析技术在疾病映射中具有良好的效果。 Kriging方法可以正确地表达空间相关性。此外,与基于模型的方法不同,这在很大程度上取决于疾病数据的假设,Kriging方法对数据更加强大。所以它可以更广泛地使用并且更具运行。更重要的是,Kriging方法可以适于插入非间断的空间结构。这可以更加基础地扩展其应用程序。最后,Kriging方法可以估计预测的不确定性,而许多确定性方法不能这样做。总之,它是一种有效的操作程序,在使用Kriging方法之前通过ESDA深入了解疾病数据。

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