A comparison of centring parameterisations of Gaussian process-based models for Bayesian computation using MCMC
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Publication:1703834
DOI10.1007/s11222-016-9700-zzbMath1384.62078DBLPjournals/sac/BassS17OpenAlexW2519109232WikidataQ59612797 ScholiaQ59612797MaRDI QIDQ1703834
Publication date: 7 March 2018
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11222-016-9700-z
Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Geostatistics (86A32)
Related Items (3)
Efficient data augmentation techniques for some classes of state space models ⋮ Multilevel linear models, Gibbs samplers and multigrid decompositions (with discussion) ⋮ Dynamically Updated Spatially Varying Parameterizations of Hierarchical Bayesian Models for Spatial Data
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