So sánh phương pháp

	Mô hình Sai số Không gian Bayes	Mô hình Độ trễ Không gian Bayes (Bayesian Spatial Lag Model - BSLM)
Lĩnh vực	Phân tích không gian	Phân tích không gian
Họ	Regression model	Regression model
Năm ra đời	1988 (classical SEM); 2009 (Bayesian formulation)	1997
Người khởi xướng	LeSage & Pace (Bayesian treatment); Anselin (classical SEM)	LeSage (1997); fully elaborated in LeSage & Pace (2009)
Loại	Bayesian spatial regression	Bayesian spatial regression
Công trình gốc	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247
Tên gọi khác	Bayesian SEM, Bayesian spatial-error regression, BSEM spatial econometrics, Bayesian spatially correlated error model	Bayesian SAR model, Bayesian spatial autoregressive model, BSLM, Bayesian SLM
Liên quan	6	5
Tóm tắt	The Bayesian Spatial Error Model (Bayesian SEM) estimates a regression in which spatially correlated disturbances are explicitly modelled through a spatial weights matrix, while all parameters — regression coefficients, spatial error autocorrelation, and error variance — receive full posterior distributions via Bayesian inference rather than point estimates.	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.