So sánh phương pháp

	Mô hình Bảng Không gian Bayes	Hồi quy Không gian Bayes
Lĩnh vực	Phân tích không gian	Phân tích không gian
Họ	Regression model	Regression model
Năm ra đời	2009–2014	1990s–2000s
Người khởi xướng	LeSage & Pace; Elhorst	Banerjee, Carlin & Gelfand (foundational treatment); building on Besag (1974) for lattice priors
Loại	Bayesian spatial panel regression	Bayesian hierarchical regression
Công trình gốc	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173
Tên gọi khác	Bayesian spatial panel, Bayesian spatial econometrics panel, BSPM, Bayesian panel spatial regression	Bayesian hierarchical spatial model, BSR, Bayesian geostatistical regression, Bayesian spatial linear model
Liên quan	5	3
Tóm tắt	The Bayesian Spatial Panel Model estimates spatial interaction effects (spatial lag, spatial error, or Durbin) in panel data using Bayesian inference via Markov Chain Monte Carlo (MCMC). It combines the ability to control for unobserved unit- and time-specific heterogeneity with principled uncertainty quantification, making it suitable for georeferenced longitudinal datasets in economics, public health, and regional science.	Bayesian Spatial Regression embeds a spatially structured random effect into a regression framework and estimates all parameters — including spatial range and variance — through posterior inference rather than point estimation. It handles spatial autocorrelation, quantifies full predictive uncertainty, and accommodates small or irregular spatial datasets via hierarchical priors.