Kriging with large data sets using sparse matrix techniques

DOI10.1080/03610919708813401zbMath0900.62681OpenAlexW2058616361MaRDI QIDQ4369366

R. Kelley Pace, Ronald Paul Barry

Publication date: 15 November 1998

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610919708813401

zbMATH Keywords

variogramgeostatisticscovariogram

Mathematics Subject Classification ID

Applications of statistics (62P99) Geostatistics (86A32)

Related Items (9)

A Spatial Interaction Model with Spatially Structured Origin and Destination Effects ⋮ Estimating sensitivity indices based on Gaussian process metamodels with compactly supported correlation functions ⋮ Fast cars ⋮ Fast kriging of large data sets with Gaussian Markov random fields ⋮ Strategies for Fitting Large, Geostatistical Data in MCMC Simulation ⋮ Efficient emulators of computer experiments using compactly supported correlation functions, with an application to cosmology ⋮ The local approximation of variograms in \(\mathcal R^2\) by covariance functions ⋮ Monte Carlo estimates of the log determinant of large sparse matrices ⋮ Compactly supported correlation functions

Uses Software

• GSLIB
• symrcm

Cites Work

• Sparse Matrices in MATLAB: Design and Implementation
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