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베이지안 공간 자기상관×베이지안 크리깅 (모델 기반 지리통계학)×
분야공간분석공간분석
계열Regression modelRegression model
기원 연도19911993–1998
창시자Besag, York & MollieDiggle, Tawn & Moyeed; Handcock & Stein
유형Bayesian hierarchical spatial modelBayesian spatial interpolation
원전Besag, J., York, J., & Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43(1), 1–20. DOI ↗Diggle, P. J., Tawn, J. A., & Moyeed, R. A. (1998). Model-based geostatistics. Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(3), 299–350. DOI ↗
별칭Bayesian spatial dependence, Bayesian LISA, Bayesian spatial clustering, BSABayesian geostatistics, model-based geostatistics, Bayesian spatial interpolation, stochastic kriging
관련65
요약Bayesian Spatial Autocorrelation embeds spatial dependence directly into a Bayesian hierarchical model. A Conditional Autoregressive (CAR) prior encodes the expectation that neighboring areas are more similar than distant ones, and posterior inference is obtained via MCMC. This approach is especially valuable in disease mapping, ecology, and regional science, where small-area estimates need borrowing strength across neighbors.Bayesian Kriging embeds classical geostatistical interpolation inside a full probabilistic framework. Instead of treating variogram parameters as fixed point estimates, it places prior distributions on them and updates these priors with observed spatial data to obtain a posterior distribution. Predictions at unsampled locations are then marginalised over this uncertainty, yielding honest predictive intervals that account for both spatial dependence and parameter uncertainty.
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