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رگرسیون فضایی محلی×مدل وقفه فضایی محلی×
حوزهتحلیل فضاییتحلیل فضایی
خانوادهRegression modelRegression model
سال پیدایش19961988 (global); 2000s (local extensions)
پدیدآورBrunsdon, Fotheringham & CharltonAnselin (global SLM, 1988); local extension via Fotheringham, Brunsdon & Charlton (GWR framework, 2002)
نوعSpatially varying coefficient regressionSpatially varying regression model
منبع بنیادینFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737215
نام‌های دیگرlocally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regressionlocal SLM, geographically weighted spatial lag model, GW-SLM, spatially varying lag model
مرتبط65
خلاصهLocal Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number.The Local Spatial Lag Model extends the classical spatial lag model by allowing both the spatial autocorrelation parameter and the regression coefficients to vary across geographic locations. Instead of one global estimate of how neighboring outcomes influence each observation, the model fits location-specific parameters using kernel-weighted local estimation, revealing spatial heterogeneity in spatial dependence.
ScholarGateمجموعه‌داده
  1. v1
  2. 2 منابع
  3. PUBLISHED
  1. v1
  2. 2 منابع
  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Local Spatial Regression · Local Spatial Lag Model. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare