Fast kriging of large data sets with Gaussian Markov random fields

DOI10.1016/j.csda.2007.09.018zbMath1452.62708OpenAlexW2070005700MaRDI QIDQ1023566

Ola G. Hössjer, Linda Werner Hartman

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.09.018

zbMATH Keywords

Markov random fieldspatial interpolationbilinear interpolationnonlattice data

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Random fields; image analysis (62M40) Geostatistics (86A32)

Related Items

Asymptotic properties of multivariate tapering for estimation and prediction, Spatial prediction with mobile sensor networks using Gaussian processes with built-in Gaussian Markov random fields, Learning with partition of unity-based kriging estimators, An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach, Kernel interpolation, GPU-accelerated simulation of massive spatial data based on the modified planar rotator model, Fully Bayesian Field Slam Using Gaussian Markov Random Fields

Uses Software

• R
• geoR
• GMRFLib

Cites Work

• Fast Sampling of Gaussian Markov Random Fields
• Approximate Bayesian inference for hierarchical Gaussian Markov random field models
• Bayesian modelling of spatial data using Markov random fields, with application to elemental composition of forest soil
• An empirical comparison of kriging methods for nonlinear spatial point prediction
• A close look at the spatial structure implied by the CAR and SAR models.
• Bayesian Geostatistical Design
• Geoadditive Models
• Kriging with large data sets using sparse matrix techniques
• Fitting Gaussian Markov Random Fields to Gaussian Fields
• The Bootstrap and Kriging Prediction Intervals
• Gaussian Markov Random Fields