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	अंतर-सामयिक स्थानिक स्वसहसंबंध	भौगोलिक भारित प्रतिगमन (GWR)
क्षेत्र	स्थानिक विश्लेषण	स्थानिक विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	1981–1992	2002
प्रवर्तक	Cliff & Ord; extended by Anselin and others	Fotheringham, Brunsdon & Charlton
प्रकार	Spatial autocorrelation statistic	Local spatial regression
मौलिक स्रोत	Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134.	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
उपनाम	STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence	GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
संबंधित	5	5
सारांश	Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss.	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.