Modeling Nonstationary and Asymmetric Multivariate Spatial Covariances via Deformations

Nonstationary Multivariate Spatial Covariance Modeling

We derive a class of matrix valued covariance functions where the direct and crosscovariance functions are Matérn. The parameters of the Matérn class are allowed to vary with location, yielding local variances, local ranges, local geometric anisotropies and local smoothnesses. We discuss inclusion of a nonconstant cross-correlation coefficient and a valid approximation. Estimation utilizes kern...

Bayesian Inference for Nonstationary Spatial Covariance Structure via Spatial Deformations

In geostatistics it is common practice to assume that the underlying spatial process is stationary and isotropic, that is the spatial distribution is unchanged when the origin of the index set is translated and the process is stationary under rotations about the origin. However in environmental problems, it is not very realistic to make such assumptions since local innuences in the correlation ...

An approach to modeling asymmetric multivariate spatial covariance structures

Modeling and Prediction of Nonstationary Spatial Processes

A Generalized Convolution Model for Multivariate Nonstationary Spatial Processes

We propose a constructive method for specifying flexible classes of nonstationary stochastic models for multivariate spatial data. The method is based upon convolutions of spatially varying covariance functions and produces mathematically valid covariance structures. This method generalizes the convolution approach suggested by Majumdar and Gelfand (2007) to extend multivariate spatial covarian...