{ "_id": "6a49d2bdb48287dcb3fda7af", "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. 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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": "2026-07-05 03:37:10 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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