Modeling Nonstationary and Asymmetric Multivariate Spatial Covariances via Deformations
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Publication:5041347
DOI10.5705/ss.202020.0156OpenAlexW3016379668MaRDI QIDQ5041347
Noel Cressie, Andrew Zammit-Mangion, Quan Vu
Publication date: 13 October 2022
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2004.08724
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- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Nonstationary modeling for multivariate spatial processes
- Generalized bootstrap method for assessment of uncertainty in semivariogram inference
- An approach to modeling asymmetric multivariate spatial covariance structures
- Surface estimation for multiple misaligned point sets
- Consistent estimates of deformed isotropic Gaussian random fields on the plane
- Constructing and fitting models for cokriging and multivariable spatial prediction
- Asymptotics for REML estimation of spatial covariance parameters
- Robust Gaussian stochastic process emulation
- Reduction problems and deformation approaches to nonstationary covariance functions over spheres
- A case study competition among methods for analyzing large spatial data
- Nonstationary multivariate process modeling through spatially varying coregionalization
- Estimating deformations of isotropic Gaussian random fields on the plane
- Multivariate spatial modeling for geostatistical data using convolved covariance functions
- Multivariate spatial mapping of soil water holding capacity with spatially varying cross-correlations
- Exploring a New Class of Non-stationary Spatial Gaussian Random Fields with Varying Local Anisotropy
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Bayesian Inference for Non-Stationary Spatial Covariance Structure via Spatial Deformations
- A Valid Matérn Class of Cross-Covariance Functions for Multivariate Random Fields With Any Number of Components
- Matérn Cross-Covariance Functions for Multivariate Random Fields
- Cross-covariance functions for multivariate random fields based on latent dimensions
- Strictly Proper Scoring Rules, Prediction, and Estimation
- Multivariate spatial covariance models: a conditional approach
- Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
- Multivariable spatial prediction
- Semiparametric estimation of cross‐covariance functions for multivariate random fields
- Deep Compositional Spatial Models