قارن الطرق

	الانحدار الموزون جغرافيًا (GWR)	انحدار المربعات الصغرى العادية (OLS)
المجال	التحليل المكاني	الاقتصاد القياسي
العائلة	Regression model	Regression model
سنة النشأة	2002	2019
صاحب الطريقة	Fotheringham, Brunsdon & Charlton	Wooldridge (textbook treatment); classical least squares
النوع	Local spatial regression	Linear regression
المصدر التأسيسي	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
الأسماء البديلة	GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
ذات صلة	5	5
الملخص	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.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).