论文标题
网格数据的不确定性：理论和全面鲁棒性测试
Uncertainty in Grid Data: A Theory and Comprehensive Robustness Test
论文作者
论文摘要
本文使用网格数据为空间政治和冲突研究做出了两个新颖的贡献。首先，它发展了一个理论，即网格数据特有的不确定性如何影响推理。其次，它在R中引入了对这种不确定性的敏感性的全面鲁棒性测试。不确定性源于（1）网格电池的正确尺寸是多少，（2）在这些网格单元之间绘制分隔线的正确位置是什么，以及（3）由于命令细胞而导致的测量误差更大的效果。作为原始网格单元的倍数，我的测试聚集了网格单元格成更大的选择。它还可以实现网格单元格聚合的不同起点（例如，是从整个地图的角度启动聚集，还是一个原始大小的一个网格单元格）以移动潜水线。我将测试应用于Tollefsen，Strand和Buhaug（2012）以证实其使用。
This article makes two novel contributions to spatial political and conflict research using grid data. First, it develops a theory of how uncertainty specific to grid data affects inference. Second, it introduces a comprehensive robustness test on sensitivity to this uncertainty, implemented in R. The uncertainty stems from (1) what is the correct size of grid cells, (2) what is the correct locations on which to draw dividing lines between these grid cells, and (3) a greater effect of measurement errors due to finer grid cells. My test aggregates grid cells into a larger size of choice as the multiple of the original grid cells. It also enables different starting points of grid cell aggregation (e.g., whether to start the aggregation from the corner of the entire map or one grid cell of the original size away from the corner) to shift the diving lines. I apply my test to Tollefsen, Strand, and Buhaug (2012) to substantiate its use.
