Bayesian Inference for Non-Stationary Spatial Covariance Structure via Spatial Deformations
通过空间变形对非平稳空间协方差结构进行贝叶斯推断
Summary In geostatistics it is common practice to assume that the underlying spatial process is stationary and isotropic, i.e. the spatial distribution is unchanged when the origin of the index set is translated and under rotation about the origin. However, in environmental problems, such assumptions are not realistic since local influences in the correlation structure of the spatial process may be found in the data. The paper proposes a Bayesian model to address the anisot-…