Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 3 of 3 for “"Conditional autoregressive (CAR) model"”.
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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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Models and methods for computationally efficient analysis of large spatial and spatio-temporal data
… devoted to computationally efficient methods and models for large spatial and spatio-temporal data. Several approximation methods to "the big n problem" are reviewed, and an extended autoregressive model, called the EAR model, is proposed as a parsimonious model that accounts for smoothness of a …
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Methods and applications for space-time data
… respectively. A nonstationary spatio-temporal model is proposed which applies the concept of the dimension expansion method in Bornn et al. (2012). The estimation of this model is investigated and simulations are conducted for both separable and nonseparable space-time covariance models. The …