Hierarchical Gaussian Processes for Spatially Dependent Model Selection
In this dissertation, we develop a model selection and estimation methodology for nonstationary spatial fields. Large, spatially correlated data often cover a vast geographical area. However, local spatial regions may have different mean and covariance structures. Our methodology accomplishes three...
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| Format: | Others |
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Virginia Tech
2018
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| Online Access: | http://hdl.handle.net/10919/84161 |