Local Linear Estimation of Spatially Varying Coefficient Models
An Improvement on the Geographically Weighted Regression Technique
Bibliographic Data
| ID | 4143338 |
|---|---|
| Authors | Ning Wang (0009-0007-8931-918X, Xi'an Jiaotong University), Chang-Lin Mei (Xi'an Jiaotong University), Changlin Mei (0000-0002-4663-7993, Xi'an Jiaotong University), Xiao-Dong Yan (Chinese Academy of Sciences), Xiaodong Yan (0009-0000-7605-5604, Chinese Academy of Sciences) |
| Year | 2008 |
| Volume | 40 |
| Issue | 4 |
| Pages | 986-1005 |
| Publication date | 2008-04-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning A Economy and Space (JOURNAL) |
| Journal identifiers | ISSN: 0308-518X • E-ISSN: 1472-3409 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1068/a3941 |
| OpenAlex | W2041868040 |
| Language | EN |
| Citations received | 11 |
| References cited | 33 |
Geographically weighted regression (GWR), as a useful method for exploring spatial non-stationarity of a regression relationship, has been applied to a variety of areas. In this method a spatially varying coefficient model is locally calibrated and the spatial-variation patterns of the locally estimated regression coefficients are taken as the main evidence of spatial nonstationarity for the underlying data-generating processes. Therefore, the validity of the analysis results drawn by GWR is closely dependent on the accuracy between the underlying coefficients and their estimates. Motivated by the local polynomial-modelling technique in statistics, we propose a local linear-based GWR for the spatially varying coefficient models, in which the coefficients are locally expanded as linear functions of the spatial coordinates and then estimated by the weighted least-squares procedure. Some theoretical and numerical comparisons with GWR are conducted and the results demonstrate that the proposed method can significantly improve GWR, not only in goodness-of-fit of the whole regression function but also in reducing bias of the coefficient estimates
Geographically Weighted Regression · Goodness of fit · Linear regression · Local regression · Mathematical analysis · Polynomial · Polynomial regression · Regression · Regression analysis · Statistics · Economic and Environmental Valuation · Mathematics · Regional Economics and Spatial Analysis · Spatial and Panel Data Analysis
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| Citations per year | 0.73 |
|---|---|
| Citation span | 2011 - 2025 (15) |
| Highly cited | No |