विधियों की तुलना करें

	स्थानीय भौगोलिक भारित प्रतिगमन (GWR)	स्थानिक लैग मॉडल (SAR / स्थानिक ऑटोरिग्रेसिव)
क्षेत्र	स्थानिक विश्लेषण	स्थानिक विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	1996	1988
प्रवर्तक	Brunsdon, Fotheringham & Charlton	Anselin (textbook formalisation); LeSage & Pace
प्रकार	Spatially varying coefficient regression	Spatial autoregressive regression
मौलिक स्रोत	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
उपनाम	GWR, geographically weighted regression, local spatial regression, spatially varying coefficient model	SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
संबंधित	5	5
सारांश	Local Geographically Weighted Regression (GWR) estimates a separate regression model at each location in the study area, allowing every coefficient to vary spatially. By weighting nearby observations more heavily than distant ones, GWR reveals how predictor-outcome relationships shift across geographic space rather than forcing a single global estimate on heterogeneous data.	The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts.