{
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  "Title": "Balanced and Spatially Balanced Sampling",
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  "Date": "2024-11-15",
  "Authors@R": "c(\nperson(\"Anton\", \"Grafström\", email = \"anton.grafstrom@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-4345-4024\")),\nperson(\"Wilmer\", \"Prentius\", email = \"wilmer.prentius@slu.se\", role = c(\"aut\"), comment = c(ORCID = \"0000-0002-3561-290X\")),\nperson(\"Jonathan\", \"Lisic\", role = c(\"ctb\"))\n)",
  "Author": "Anton Grafström [aut, cre]\n(<https://orcid.org/0000-0002-4345-4024>), Wilmer Prentius\n[aut] (<https://orcid.org/0000-0002-3561-290X>), Jonathan Lisic\n[ctb]",
  "Maintainer": "Anton Grafström <anton.grafstrom@gmail.com>",
  "Description": "Select balanced and spatially balanced probability samples\nin multi-dimensional spaces with any prescribed inclusion\nprobabilities. It contains fast (C++ via Rcpp) implementations\nof the included sampling methods. The local pivotal method by\nGrafström, Lundström and Schelin (2012)\n<doi:10.1111/j.1541-0420.2011.01699.x> and spatially correlated\nPoisson sampling by Grafström (2012)\n<doi:10.1016/j.jspi.2011.07.003> are included. Also the cube\nmethod (for balanced sampling) and the local cube method (for\ndoubly balanced sampling) are included, see Grafström and Tillé\n(2013) <doi:10.1002/env.2194>.",
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