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ベイズ空間回帰×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 modelRegression model
提唱年1990s–2000s1988
提唱者Banerjee, Carlin & Gelfand (foundational treatment); building on Besag (1974) for lattice priorsAnselin (textbook formalisation); LeSage & Pace
種類Bayesian hierarchical regressionSpatial autoregressive regression
原典Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗
別名Bayesian hierarchical spatial model, BSR, Bayesian geostatistical regression, Bayesian spatial linear modelSAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
関連35
概要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.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.
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ScholarGate手法を比較: Bayesian Spatial Regression · Spatial Lag Model. 2026-06-15に以下より取得 https://scholargate.app/ja/compare