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Adaptive Gaussian Predictive Process Models for Large Spatial Datasets

Large point referenced datasets occur frequently in the environmental and natural sciences. Use of Bayesian hierarchical spatial models for analyzing these datasets is undermined by onerous computational burdens associated with parameter estimation. Low-rank spatial process models attempt to resolve...

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Détails bibliographiques
Auteurs principaux: Guhaniyogi, Rajarshi, Finley, Andrew O., Banerjee, Sudipto, Gelfand, Alan E.
Format: Artigo
Langue:Inglês
Publié: 2011
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC3268014/
https://ncbi.nlm.nih.gov/pubmed/22298952
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/env.1131
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