成分数据的变系数地理加权空间滞后模型  

A varying coefficient geographically weighted spatial lag model for compositional data

作　　者：黄婷婷 Huang Tingting(School of Statistics,Capital University of Economics and Business,Beijing 100070,China)

机构地区：[1]首都经济贸易大学统计学院,北京100070

出　　处：《北京航空航天大学学报》2024年第7期2256-2264,共9页Journal of Beijing University of Aeronautics and Astronautics

基　　金：北京市自然科学基金(9224032)。

摘　　要：针对已有模型无法刻画面类型空间依赖下成分数据的空间异质性,提出模型参数可变的成分数据空间自回归模型。通过假定空间滞后参数、成分型系数、数值型系数为位置坐标的函数,允许空间效应和变量关系在全局空间上非均匀分布。基于等距对数比(ilr)变换、工具变量法和局部线性地理加权法,对模型参数进行估计。数值模拟实验表明:所提出模型的表现优于已有的成分数据空间自回归模型,并且参数估计量是有效的。基于一组实际数据,说明所提模型的实用性。When it comes to area data with compositional factors,existing regression models seldom ever take spatial heterogeneity into account.To solve the problem,a compositional spatial autoregressive model with varying coefficients is proposed.By assuming that the spatial lag parameter,the compositional coefficient,and the numerical coefficient are functions of the location coordinates,the new model permits spatial effects and linear interactions between covariates and response to change in space.Based on isometric log-ratio(ILR) transformation,instrumental variables and local linear geographically weighted method,the parameters are estimated.The simulation study shows that the proposed model is superior to the existing spatial autoregressive model for compositional data,and the parameters estimation are effective.The utility of the proposed model is demonstrated by a real data set.

关 键 词：成分数据 面数据 空间异质性 等距对数比变换 地理加权模型 

分 类 号：F222[经济管理—国民经济]