Bayesian modeling for large spatial datasets
نویسندگان
چکیده
منابع مشابه
Bayesian Modeling for Large Spatial Datasets.
We focus upon flexible Bayesian hierarchical models for scientific data available at geo-coded locations. Investigators are increasingly turning to spatial process models to analyze such datasets. These models are customarily estimated using Markov Chain Monte Carlo (MCMC) methods, which have become especially popular for spatial modeling, given their flexibility and power to fit models that wo...
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Datasets in the fields of climate and environment are often very large and irregularly spaced. To model such datasets, the widely used Gaussian process models in spatial statistics face tremendous challenges due to the prohibitive computational burden. Various approximation methods have been introduced to reduce the computational cost. However, most of them rely on unrealistic assumptions of th...
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ژورنال
عنوان ژورنال: Wiley Interdisciplinary Reviews: Computational Statistics
سال: 2011
ISSN: 1939-5108
DOI: 10.1002/wics.187