论文标题
位置不确定性下的快速地理统计推论：分析DHS家庭调查数据
Fast geostatistical inference under positional uncertainty: Analysing DHS household survey data
论文作者
论文摘要
来自人口统计和健康调查（DHS）计划的家庭调查数据与GPS坐标一起发布。但是，几乎所有此类数据的地统计分析都忽略了已发表的GPS坐标是随机位移（抖动）。在此简短报告中，我们开发了一个地理模型，该模型在分析DHS调查时说明了位置不确定性，并使用模板模型构建器提供了快速实现。关键的重点是在位置不确定性下对高斯随机场的推断，我们的方法适用于高斯和非高斯的可能性。具有二项式观察模型的仿真研究表明，在更准确的参数估计和改进的预测措施方面，新方法的性能均匀或更好地忽略抖动的方法。我们证明，在更强的抖动下，改进将更大。肯尼亚避孕药使用的分析表明，该方法在实践中易于使用。
Household survey data from the Demographic and Health Surveys (DHS) Program is published with GPS coordinates. However, almost all geostatistical analyses of such data ignore that the published GPS coordinates are randomly displaced (jittered). In this short report, we develop a geostatistical model that accounts for the positional uncertainty when analysing DHS surveys, and provide a fast implementation using Template Model Builder. The key focus is inference with Gaussian random fields under positional uncertainty, and our approach works for both Gaussian and non-Gaussian likelihoods. A simulation study with a binomial observation model shows that the new approach performs equally or better than the common approach of ignoring jittering, both in terms of more accurate parameter estimates and improved predictive measures. We demonstrate that the improvement would be larger under stronger jittering. An analysis of contraceptive use in Kenya shows that the approach is fast and easy to use in practice.
