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Prostorno Bejzovo zaključivanje×Hierarchical Bayesian Inference×
OblastBajesovska statistikaBajesovska statistika
PorodicaBayesian methodsBayesian methods
Godina nastanka19911972 (Lindley & Smith); consolidated 1995–2013
TvoracBesag, York & Mollie (CAR prior, 1991); Gelfand & colleagues (Bayesian geostatistics, 1990s)Lindley & Smith; Gelman et al.
TipBayesian hierarchical spatial modelBayesian multilevel model
Temeljni izvorBanerjee, S., Carlin, B. P. & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
Drugi naziviBayesian spatial analysis, Bayesian geostatistics, spatial Bayesian modeling, Bayesian areal modelingmultilevel Bayesian modeling, Bayesian hierarchical model, nested Bayesian model, partial pooling model
Srodne26
SažetakSpatial 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.Hierarchical Bayesian inference is a probabilistic modeling framework that organises parameters into levels, placing priors on the group-level parameters and hyperpriors on the parameters governing those priors. It enables partial pooling of information across groups, balancing the extremes of treating each group as independent or merging them into a single estimate.
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ScholarGateUporedite metode: Spatial Bayesian Inference · Hierarchical Bayesian Inference. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare