摘要
采用Moran指标分析截面数据空间自相关性.针对具有空间自相关截面数据缺失插值问题,分别建立一阶空间自回归插值模型与克立格方法插值模型,在此基础上建立截面数据的组合插值模型,并用信息熵法确定组合插值模型的加权系数.用2003年福建部分市县城镇化水平的截面数据建立插值模型实证研究结果表明:组合插值模型的效果优于单项插值模型的效果.
Spatial autocorrelation of cross-sectional data is analyzed by Moran indicator. The first-order spatial autoregressive interpolation model and Kriging interpolation model, based on cross-sectional data with spatial autocorrelation, are established. A combination interpolation model is constructed by the results of the two models, The weights of the combination model are obtained by information entropy. An empirical research is carried out by using some areas＇ urbanization in Fujian, 2003. It is found that the effect of the combination interpolation model is better than that of the single interpolation model.
出处
《数理统计与管理》
CSSCI
北大核心
2009年第2期237-243,共7页
Journal of Applied Statistics and Management
关键词
截面数据
空间自相关
组合插值模型
信息熵
cross-sectional data, spatial autocorrelation, combination interpolation model, information entropy
