ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

面板地理加权回归 (Panel GWR)×地理加权回归 (GWR)×
领域空间分析空间分析
方法族Regression modelRegression model
起源年份2000s–2010s2002
提出者Fotheringham, Brunsdon & Charlton (foundational GWR); panel extension developed in spatial econometrics literatureFotheringham, Brunsdon & Charlton
类型Local spatial regression with panel structureLocal spatial regression
开创性文献Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
别名Panel GWR, PGWR, spatiotemporal GWR, geographically weighted panel regressionGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
相关45
摘要Panel Geographically Weighted Regression (Panel GWR) extends the standard GWR framework to panel data, allowing regression coefficients to vary both across geographic locations and over time. It captures spatially non-stationary relationships in longitudinal or repeated-measures spatial datasets, combining local spatial estimation with panel-data controls for unit-specific heterogeneity.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 1 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Panel Geographically Weighted Regression · Geographically Weighted Regression. 于 2026-06-19 检索自 https://scholargate.app/zh/compare