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Mô phỏng Bootstrap Không gian×Suy luận Bayes không gian×
Lĩnh vựcBayesBayes
HọBayesian methodsBayesian methods
Năm ra đời1990s–2000s1991
Người khởi xướngLahiri and others, building on Efron's bootstrap (1979)Besag, York & Mollie (CAR prior, 1991); Gelfand & colleagues (Bayesian geostatistics, 1990s)
LoạiResampling / simulationBayesian hierarchical spatial model
Công trình gốcLahiri, S. N. (2003). Resampling Methods for Dependent Data. Springer. ISBN: 978-0387009285Banerjee, S., Carlin, B. P. & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173
Tên gọi khácspatial block bootstrap, spatial resampling, geostatistical bootstrap, bootstrap for spatial dataBayesian spatial analysis, Bayesian geostatistics, spatial Bayesian modeling, Bayesian areal modeling
Liên quan42
Tóm tắtSpatial bootstrap simulation is a resampling technique designed for spatially dependent data. By resampling contiguous spatial blocks rather than independent observations, it preserves the local autocorrelation structure of the data and yields valid estimates of sampling variability for statistics computed on geographic or lattice observations.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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ScholarGateSo sánh phương pháp: Spatial Bootstrap Simulation · Spatial Bayesian Inference. Truy cập ngày 2026-06-15 từ https://scholargate.app/vi/compare