{
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  "Package": "aclhs",
  "Title": "Autocorrelated Conditioned Latin Hypercube Sampling",
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  "Authors@R": "c(\nperson(\"Van Huong\", \"Le\", , \"vanle@udel.edu\", role = c(\"aut\", \"ctb\"),\ncomment = c(ORCID = \"0000-0002-3700-9987\")),\nperson(\"Rodrigo\", \"Vargas\", , \"rvargasr@asu.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-6829-5333\")),\nperson(\"Gabriel\", \"Laboy\", , \"glaboy1@asu.edu\", role = c(\"ctb\", \"cre\"),\ncomment = c(ORCID = \"0009-0004-1538-5035\"))\n)",
  "Description": "Implementation of the autocorrelated conditioned Latin\nHypercube Sampling (acLHS) algorithm for 1D (time-series) and\n2D (spatial) data. The acLHS algorithm is an extension of the\nconditioned Latin Hypercube Sampling (cLHS) algorithm that\nallows sampled data to have similar correlative and statistical\nfeatures of the original data. Only a properly formatted\ndataframe needs to be provided to yield subsample indices from\nthe primary function. For more details about the cLHS\nalgorithm, see Minasny and McBratney (2006),\n<doi:10.1016/j.cageo.2005.12.009>. For acLHS, see Le and Vargas\n(2024) <doi:10.1016/j.cageo.2024.105539>.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/vargaslab/acLHS",
  "BugReports": "https://github.com/vargaslab/acLHS/issues",
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  "Repository": "https://vargaslab.r-universe.dev",
  "Date/Publication": "2025-11-01 01:11:57 UTC",
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    "User": "root"
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  "Author": "Van Huong Le [aut, ctb] (ORCID:\n<https://orcid.org/0000-0002-3700-9987>),\nRodrigo Vargas [aut] (ORCID: <https://orcid.org/0000-0001-6829-5333>),\nGabriel Laboy [ctb, cre] (ORCID:\n<https://orcid.org/0009-0004-1538-5035>)",
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    "name": "Rodrigo Vargas",
    "description": "Professor at Arizona State University. Ecosystem Ecologist and carbon cycle scientist. Associate Editor @AGUbiogeo."
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      "page": "aclhs",
      "title": "Get subsample indices using the acLHS algorithm.",
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        "aclhs"
      ]
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