{ "_id": "6ad09f67576abc75bd5cdd14", "Package": "kergp", "Type": "Package", "Title": "Gaussian Process Laboratory", "Version": "0.5.8", "Date": "2024-11-19", "Authors@R": "c(person(given = \"Yves\", family = \"Deville\", role = \"aut\",\nemail = \"deville.yves@alpestat.com\",\ncomment = c(ORCID = \"0000-0002-1233-488X\")),\nperson(given = \"David\", family = \"Ginsbourger\", role = \"aut\",\nemail = \"david.ginsbourger@stat.unibe.ch\",\ncomment = c(ORCID = \"0000-0003-2724-2678\")),\nperson(given = \"Olivier\", family = \"Roustant\", role = c(\"aut\", \"cre\"),\nemail = \"roustant@insa-toulouse.fr\"),\nperson(given = \"Nicolas\", family = \"Durrande\", role = \"ctb\"))", "Description": "Gaussian process regression with an emphasis on kernels.\nQuantitative and qualitative inputs are accepted. Some\npre-defined kernels are available, such as radial or tensor-sum\nfor quantitative inputs, and compound symmetry, low rank, group\nkernel for qualitative inputs. The user can define new kernels\nand composite kernels through a formula mechanism. Useful\nmethods include parameter estimation by maximum likelihood,\nsimulation, prediction and leave-one-out validation.", "License": "GPL-3", "RoxygenNote": "6.0.1", "Collate": "'CovFormulas.R' 'allGenerics.R' 'checkGrad.R' 'covComp.R'\n'covMan.R' 'covQual.R' 'q1CompSymm.R' 'q1Symm.R' 'q1LowRank.R'\n'covQualNested.R' 'covQualOrd.R' 'covRadial.R' 'covTS.R'\n'covTP.R' 'covANOVA.R' 'covZZAll.R' 'gp.R' 'kFuns.R'\n'kernelNorm.R' 'kernels1d_Call.R' 'logLikFuns.R' 'methodGLS.R'\n'methodMLE.R' 'miscUtils.R' 'prinKrige.R' 'q1Diag.R'\n'simulate_gp.R' 'warpFuns.R'", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-15 09:18:53 UTC", "User": "root" }, "Author": "Yves Deville [aut] (),\nDavid Ginsbourger [aut]\n(), Olivier Roustant\n[aut, cre], Nicolas Durrande [ctb]", "Maintainer": "Olivier Roustant ", "Config/pak/sysreqs": "cmake make libuv1-dev", "Repository": "https://roustant.r-universe.dev", "Date/Publication": "2024-11-19 14:40:03 UTC", "RemoteUrl": "https://github.com/cran/kergp", 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'\"covANOVA\"'", "topics": [ "coef,covANOVA-method", "coef<-,covANOVA,numeric-method", "coefLower,covANOVA-method", "coefLower<-,covANOVA-method", "coefUpper,covANOVA-method", "coefUpper<-,covANOVA-method", "covANOVA-class", "covMat,covANOVA-method", "npar,covANOVA-method", "scores,covANOVA-method", "show,covANOVA-method", "varVec,covANOVA-method" ] }, { "page": "covComp", "title": "Creator for the Class '\"covComp\"' for Composite Covariance Kernels", "topics": [ "covComp" ] }, { "page": "covComp-class", "title": "Class '\"covComp\"'", "topics": [ "as.list,covComp-method", "checkX,covComp,data.frame-method", "coef,covComp-method", "coef<-,covComp,numeric-method", "coefLower,covComp-method", "coefUpper,covComp-method", "covComp-class", "covMat,covComp-method", "inputNames<-,covComp,character-method", "scores,covComp-method", "show,covComp-method", "varVec,covComp-method" ] }, { "page": "covMan", "title": "Creator Function for 'covMan' Objects", "topics": [ "covMan" ] }, { "page": "covMan-class", "title": "Class '\"covMan\"'", "topics": [ "coef<-,covMan,numeric-method", "coefLower,covMan-method", "coefLower<-,covMan-method", "coefUpper,covMan-method", "coefUpper<-,covMan-method", "coerce,covMan,function-method", "covMan-class", "scores,covMan-method", "show,covMan-method" ] }, { "page": "covMat", "title": "Generic Function: Covariance or Cross-Covariance Matrix Between two Sets of Locations", "topics": [ "covMat" ] }, { "page": "covMat-methods", "title": "Covariance Matrix for a Covariance Kernel Object", "topics": [ "covMat,covMan-method", "covMat,covTS-method" ] }, { "page": "covOrd", "title": "Warping-Based Covariance for an Ordinal Input", "topics": [ "covOrd" ] }, { "page": "covOrd-class", "title": "Class '\"covOrd\"'", "topics": [ "checkX,covOrd,data.frame-method", "checkX,covOrd,matrix-method", "coef,covOrd-method", "coef<-,covOrd,numeric-method", "coefLower,covOrd-method", "coefLower<-,covOrd-method", "coefUpper,covOrd-method", 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Class '\"covRadial\"'", "topics": [ "covRadial" ] }, { "page": "covRadial-class", "title": "Class '\"covRadial\"'", "topics": [ "coef,covRadial-method", "coef<-,covRadial,numeric-method", "coefLower,covRadial-method", "coefLower<-,covRadial-method", "coefUpper,covRadial-method", "coefUpper<-,covRadial-method", "covMat,covRadial-method", "covRadial-class", "npar,covRadial-method", "scores,covRadial-method", "show,covRadial-method", "varVec,covRadial-method" ] }, { "page": "covTP", "title": "Creator for the Class '\"covTP\"'", "topics": [ "covTP" ] }, { "page": "covTP-class", "title": "Class '\"covTP\"'", "topics": [ "coef,covTP-method", "coef<-,covTP,numeric-method", "coefLower,covTP-method", "coefLower<-,covTP-method", "coefUpper,covTP-method", "coefUpper<-,covTP-method", "covMat,covTP-method", "covTP-class", "npar,covTP-method", "scores,covTP-method", "show,covTP-method", "varVec,covTP-method" ] }, { "page": "covTS", "title": "Creator Function for 'covTS' Objects", "topics": [ "covTS" 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Function: Names of the Inputs of a Covariance Kernel", "topics": [ "inputNames", "inputNames,covAll-method", "inputNames<-", "inputNames<-,covAll,character-method", "inputNames<-,covAll-method" ] }, { "page": "k1Kerns", "title": "Predefined covMan Objects for 1D Kernels", "topics": [ "k1Exp", "k1Gauss", "k1Matern3_2", "k1Matern5_2", "k1PowExp" ] }, { "page": "k1Funs", "title": "One-Dimensional Classical Covariance Kernel Functions", "topics": [ "k1Fun1Cos", "k1Fun1Exp", "k1Fun1Gauss", "k1Fun1Matern3_2", "k1Fun1Matern5_2", "k1Fun1PowExp", "k1FunExp", "k1FunGauss", "k1FunMatern3_2", "k1FunMatern5_2", "k1FunPowExp" ] }, { "page": "kernelName", "title": "Name of the One-Dimensional Kernel in a Composite Kernel Object", "topics": [ "kernelName" ] }, { "page": "kGauss", "title": "Gauss (Squared-Exponential) Kernel", "topics": [ "kGauss", "kSE" ] }, { "page": "kMatern", "title": "Matérn Kernels", "topics": [ "kExp", "kMatern" ] }, { "page": "MLE", "title": "Generic Function: Maximum Likelihood Estimation of a Gaussian Process Model", "topics": [ "mle" ] }, { "page": "MLE-methods", "title": "Maximum Likelihood Estimation of Gaussian Process Model Parameters", "topics": [ "mle,covAll-method", "mle-methods" ] }, { "page": "npar", "title": "Generic function: Number of Free Parameters in a Covariance Kernel", "topics": [ "npar" ] }, { "page": "npar-methods", "title": "Number of Parameters for a Covariance Kernel Object", "topics": [ "npar,covMan-method", "npar,covTS-method" ] }, { "page": "optimMethods", "title": "Optimization Methods (or Algorithms) for the 'mle' Method", "topics": [ "optimMethods" ] }, { "page": "parMap", "title": "Generic Function: Map the Parameters of a Composite Covariance Kernel", "topics": [ "parMap" ] }, { "page": "parMap-methods", "title": "Map the Parameters of a Structure on the Inputs and Kernel Parameters", "topics": [ "parMap,covTS-method" ] }, { "page": "parNamesSymm", "title": "Vector of Names for the General 'Symm' Parameterisation", 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