constrainedKriging: Constrained, Covariance-Matching Constrained and Universal Point or Block Kriging

Provides functions for efficient computation of non-linear spatial predictions with local change of support (Hofer, C. and Papritz, A. (2011) "constrainedKriging: An R-package for customary, constrained and covariance-matching constrained point or block kriging" <doi:10.1016/j.cageo.2011.02.009>). This package supplies functions for two-dimensional spatial interpolation by constrained (Cressie, N. (1993) "Aggregation in geostatistical problems" <doi:10.1007/978-94-011-1739-5_3>), covariance-matching constrained (Aldworth, J. and Cressie, N. (2003) "Prediction of nonlinear spatial functionals" <doi:10.1016/S0378-3758(02)00321-X>) and universal (external drift) Kriging for points or blocks of any shape from data with a non-stationary mean function and an isotropic weakly stationary covariance function. The linear spatial interpolation methods, constrained and covariance-matching constrained Kriging, provide approximately unbiased prediction for non-linear target values under change of support. This package extends the range of tools for spatial predictions available in R and provides an alternative to conditional simulation for non-linear spatial prediction problems with local change of support.

Package details

AuthorChristoph Hofer [aut], Andreas Papritz [ctb, cre]
MaintainerAndreas Papritz <papritz@retired.ethz.ch>
LicenseGPL (>= 2)
Version0.2-11
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("constrainedKriging")

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constrainedKriging documentation built on April 3, 2025, 5:35 p.m.