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Spatial Gibbs Sampling

Spatial Gibbs sampling applies the Gibbs sampler — a coordinate-wise Markov chain Monte Carlo algorithm — to models where observations are arranged in space and nearby locations are statistically dependent. By exploiting the conditional independence implied by a spatial neighbourhood structure, each site is updated one at a time given its neighbours, making posterior inference tractable for Markov random fields, Gaussian random fields, and hierarchical geostatistical models.

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Spatial Gibbs Sampling for Markov Random Fields and Geostatistical Models

Taksonomisk metoderegistrering · bayesian / bayesian

Geman, S. & Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6), 721–741. · DOI 10.1109/TPAMI.1984.4767596
Rue, H. & Held, L. (2005). Gaussian Markov Random Fields: Theory and Applications. Chapman & Hall/CRC. · ISBN 978-1584884323

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Same method familyBayesian Hierarchical Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketGibbs Samplingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSpatial Bayesian Inferencemachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSpatial MCMCmachine-suggested · Relational suggestion, not evidence.