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ベイズ地理的加重回帰 (BGWR)×局所空間回帰×
分野空間分析空間分析
系統Regression modelRegression model
提唱年20071996
提唱者Wheeler & Calder (2007); Finley (2011)Brunsdon, Fotheringham & Charlton
種類Bayesian spatially varying coefficient regressionSpatially varying coefficient 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. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
別名BGWR, Bayesian GWR, Bayesian spatially varying coefficient model, Bayesian local regressionlocally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regression
関連56
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.Local Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number.
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ScholarGate手法を比較: Bayesian Geographically Weighted Regression · Local Spatial Regression. 2026-06-17に以下より取得 https://scholargate.app/ja/compare