{ "_id": "6adf19945e3add5cd78ef6df", "Package": "magi", "Type": "Package", "Title": "MAnifold-Constrained Gaussian Process Inference", "Version": "1.2.5", "Date": "2025-10-22", "Authors@R": "c(person(given = \"Shihao\",\nfamily = \"Yang\",\nrole = c(\"aut\", \"cre\"),\nemail = \"shihao.yang@isye.gatech.edu\",\ncomment = c(ORCID = \"0000-0003-3910-4969\")),\nperson(given = \"Samuel W.K.\",\nfamily = \"Wong\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-7325-7267\")),\nperson(given = \"S.C.\",\nfamily = \"Kou\",\nrole = c(\"ctb\", \"cph\"),\ncomment = c(role = \"Contributor of MAGI method development\"))\n)", "Encoding": "UTF-8", "Description": "Provides fast and accurate inference for the parameter\nestimation problem in Ordinary Differential Equations,\nincluding the case when there are unobserved system components.\nImplements the MAGI method (MAnifold-constrained Gaussian\nprocess Inference) of Yang, Wong, and Kou (2021)\n. 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