Multivariate spatial meta kriging
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Publication:1726740
DOI10.1016/j.spl.2018.04.017zbMath1407.62345OpenAlexW2801741420WikidataQ91130578 ScholiaQ91130578MaRDI QIDQ1726740
Rajarshi Guhaniyogi, Sudipto Banerjee
Publication date: 20 February 2019
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://escholarship.org/uc/item/1198466s
Bayesian inferencemultivariate Gaussian processspatial stochastic processlinear model coregionalizationpoint-referenced dataspatial meta kriging
Directional data; spatial statistics (62H11) Inference from spatial processes (62M30) Bayesian inference (62F15)
Related Items
Distributed Bayesian inference in massive spatial data, Low-rank multi-parametric covariance identification
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Cites Work
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- Modeling complex spatial dependencies: low-rank spatially varying cross-covariances with application to soil nutrient data
- Fixed-domain asymptotic properties of tapered maximum likelihood estimators
- Nonstationary multivariate process modeling through spatially varying coregionalization
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Handbook of Spatial Statistics
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Hierarchical Spatial Modeling of Additive and Dominance Genetic Variance for Large Spatial Trial Datasets
- Approximating Likelihoods for Large Spatial Data Sets
- Hierarchical Spatial Process Models for Multiple Traits in Large Genetic Trials
- Matérn Cross-Covariance Functions for Multivariate Random Fields
- Strictly Proper Scoring Rules, Prediction, and Estimation
- Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets