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  "Type": "Package",
  "Title": "Methods and Reproducible Workflows for Partial Least Squares\nwith Missing Data",
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  "Date": "2026-04-07",
  "Authors@R": "c(\nperson(\"Titin Agustin\", \"Nengsih\", role = \"aut\"),\nperson(\"Frederic\", \"Bertrand\", role = c(\"aut\", \"cre\"), email = \"frederic.bertrand@lecnam.net\"),\nperson(\"Myriam\", \"Maumy-Bertrand\", role = \"aut\"))",
  "Author": "Titin Agustin Nengsih [aut], Frederic Bertrand [aut, cre],\nMyriam Maumy-Bertrand [aut]",
  "Maintainer": "Frederic Bertrand <frederic.bertrand@lecnam.net>",
  "Description": "Methods-first tooling for reproducing and extending the\npartial least squares regression studies on incomplete data\ndescribed in Nengsih et al. (2019)\n<doi:10.1515/sagmb-2018-0059>. The package provides simulation\nhelpers, missingness generators, imputation wrappers,\ncomponent-selection utilities, real-data diagnostics, and\nreproducible study orchestration for Nonlinear Iterative\nPartial Least Squares (NIPALS)-Partial Least Squares (PLS)\nworkflows.",
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      "table": false,
      "tojson": false
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      "class": [
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