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ベイズ汎用クリギング×地理的に重み付けされた回帰分析 (GWR)×
分野空間分析空間分析
系統Regression modelRegression model
提唱年1990s–2000s2002
提唱者Diggle, Tawn & Moyeed; Kitanidis; Handcock & SteinFotheringham, Brunsdon & Charlton
種類Bayesian geostatistical interpolation with trendLocal spatial regression
原典Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
別名BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal krigingGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
関連65
概要Bayesian Universal Kriging (BUK) extends classical universal kriging by placing prior distributions on trend coefficients and spatial covariance parameters, then propagating full posterior uncertainty into predictions. It interpolates spatially referenced continuous data while simultaneously estimating large-scale deterministic trends driven by covariates and small-scale stochastic spatial dependence, yielding prediction intervals that honestly account for both parameter and interpolation uncertainty.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
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ScholarGate手法を比較: Bayesian Universal Kriging · Geographically Weighted Regression. 2026-06-18に以下より取得 https://scholargate.app/ja/compare