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  "Package": "GPTreeO",
  "Title": "Dividing Local Gaussian Processes for Online Learning Regression",
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  "Authors@R": "c(\nperson(given = \"Timo\",\nfamily = \"Braun\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0001-0965-8285\"),\nemail = \"gptreeo.timo.braun@gmail.com\"),\nperson(given = \"Anders\",\nfamily = \"Kvellestad\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-5267-7705\")),\nperson(given = \"Riccardo\",\nfamily = \"De Bin\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0002-7441-6880\")))",
  "Maintainer": "Timo Braun <gptreeo.timo.braun@gmail.com>",
  "Description": "We implement and extend the Dividing Local Gaussian\nProcess algorithm by Lederer et al. (2020)\n<doi:10.48550/arXiv.2006.09446>. Its main use case is in online\nlearning where it is used to train a network of local GPs\n(referred to as tree) by cleverly partitioning the input space.\nIn contrast to a single GP, 'GPTreeO' is able to deal with\nlarger amounts of data. The package includes methods to create\nthe tree and set its parameter, incorporating data points from\na data stream as well as making joint predictions based on all\nrelevant local GPs.",
  "License": "MIT + file LICENSE",
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  "Repository": "https://timo-braun.r-universe.dev",
  "Date/Publication": "2024-10-16 16:06:21 UTC",
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    "User": "root"
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  "Author": "Timo Braun [aut, cre] (ORCID: <https://orcid.org/0009-0001-0965-8285>),\nAnders Kvellestad [aut] (ORCID:\n<https://orcid.org/0000-0002-5267-7705>),\nRiccardo De Bin [ctb] (ORCID: <https://orcid.org/0000-0002-7441-6880>)",
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  "_published": "2026-05-22T08:42:25.417Z",
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    "GPTree",
    "WrappedDiceKrigingGP",
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        "Changes in \\texttt",
        "Changes in \\texttt",
        "Optional and advanced features"
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      "modified": "2024-10-01 15:30:53",
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