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空間的近似ベイズ計算×空間ベイズ推論×
分野ベイズベイズ
系統Bayesian methodsBayesian methods
提唱年2002 (spatial extensions from mid-2000s)1991
提唱者Diggle & Gratton (implicit statistical models, 1984); Beaumont, Zhang & Balding (ABC formalization, 2002)Besag, York & Mollie (CAR prior, 1991); Gelfand & colleagues (Bayesian geostatistics, 1990s)
種類likelihood-free Bayesian inferenceBayesian hierarchical spatial model
原典Beaumont, M. A., Zhang, W., & Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025–2035. DOI ↗Banerjee, S., Carlin, B. P. & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173
別名Spatial ABC, ABC for spatial data, likelihood-free Bayesian spatial inference, simulation-based spatial inferenceBayesian spatial analysis, Bayesian geostatistics, spatial Bayesian modeling, Bayesian areal modeling
関連42
概要Spatial Approximate Bayesian Computation (Spatial ABC) is a likelihood-free Bayesian inference framework for spatial data models whose likelihood function is intractable or too expensive to evaluate. It draws candidate parameters from a prior, simulates spatially structured datasets under those parameters, and accepts only the draws whose simulated spatial summary statistics closely match the observed data, thereby building an approximate posterior over model parameters.Spatial Bayesian inference applies Bayesian hierarchical modeling to data indexed by geographic location. By placing structured spatial priors on location-specific random effects, the model borrows information from neighboring regions or nearby points, producing smooth, uncertainty-quantified maps of any spatially varying outcome — disease rates, pollution levels, species abundance, or environmental risk.
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ScholarGate手法を比較: Spatial Approximate Bayesian Computation · Spatial Bayesian Inference. 2026-06-15に以下より取得 https://scholargate.app/ja/compare