So sánh phương pháp

	Mô hình Độ trễ Không gian Bayes (Bayesian Spatial Lag Model - BSLM)	Hồi quy Trọng số Địa lý (GWR)
Lĩnh vực	Phân tích không gian	Phân tích không gian
Họ	Regression model	Regression model
Năm ra đời	1997	2002
Người khởi xướng	LeSage (1997); fully elaborated in LeSage & Pace (2009)	Fotheringham, Brunsdon & Charlton
Loại	Bayesian spatial regression	Local spatial regression
Công trình gốc	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Tên gọi khác	Bayesian SAR model, Bayesian spatial autoregressive model, BSLM, Bayesian SLM	GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Liên quan	5	5
Tóm tắt	The Bayesian Spatial Lag Model (BSLM) extends the classical spatial autoregressive (SAR) regression by placing prior distributions over all parameters and recovering full posterior distributions via MCMC sampling. It explicitly accounts for spatial dependence — the outcome in one location is partly driven by outcomes in neighboring locations — and yields uncertainty-quantified estimates of both regression coefficients and the spatial autocorrelation parameter rho.	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.