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  "Title": "Constrained, Covariance-Matching Constrained and Universal Point\nor Block Kriging",
  "Date": "2025-02-04",
  "Authors@R": "c(person(\"Christoph\", \"Hofer\", role = \"aut\", email = \"christoph.hofer@alumni.ethz.ch\"),        person(\"Andreas\", \"Papritz\", role = c(\"ctb\", \"cre\"), email =  \"papritz@retired.ethz.ch\" ))",
  "Description": "Provides functions for efficient computation of non-linear\nspatial predictions with local change of support (Hofer, C. and\nPapritz, A. (2011) \"constrainedKriging: An R-package for\ncustomary, constrained and covariance-matching constrained\npoint or block kriging\" <doi:10.1016/j.cageo.2011.02.009>).\nThis package supplies functions for two-dimensional spatial\ninterpolation by constrained (Cressie, N. (1993) \"Aggregation\nin geostatistical problems\" <doi:10.1007/978-94-011-1739-5_3>),\ncovariance-matching constrained (Aldworth, J. and Cressie, N.\n(2003) \"Prediction of nonlinear spatial functionals\"\n<doi:10.1016/S0378-3758(02)00321-X>) and universal (external\ndrift) Kriging for points or blocks of any shape from data with\na non-stationary mean function and an isotropic weakly\nstationary covariance function.  The linear spatial\ninterpolation methods, constrained and covariance-matching\nconstrained Kriging, provide approximately unbiased prediction\nfor non-linear target values under change of support.  This\npackage extends the range of tools for spatial predictions\navailable in R and provides an alternative to conditional\nsimulation for non-linear spatial prediction problems with\nlocal change of support.",
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