手法を比較

	ベイズ地理的加重回帰 (BGWR)	空間ラグモデル（SAR / 空間自己回帰）
分野	空間分析	空間分析
系統	Regression model	Regression model
提唱年	2007	1988
提唱者	Wheeler & Calder (2007); Finley (2011)	Anselin (textbook formalisation); LeSage & Pace
種類	Bayesian spatially varying coefficient regression	Spatial autoregressive regression
原典	Finley, A. O. (2011). Comparing spatially-varying coefficients models for analysis of ecological data with non-stationary and anisotropic residual dependence. Methods in Ecology and Evolution, 2(2), 143-154.	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
別名	BGWR, Bayesian GWR, Bayesian spatially varying coefficient model, Bayesian local regression	SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
関連	5	5
概要	Bayesian Geographically Weighted Regression combines the spatially varying coefficient framework of GWR with Bayesian inference, placing Gaussian process priors on the locally varying regression coefficients. This yields full posterior distributions over each coefficient at every location, providing principled uncertainty quantification rather than only point estimates.	The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts.