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  "Date": "2025-09-12",
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  "Title": "Bootstrap Hyperparameter Selection for PLS Models and Extensions",
  "Authors@R": "c(\nperson(given = \"Frederic\", family= \"Bertrand\", role = c(\"cre\", \"aut\"), email = \"frederic.bertrand@lecnam.net\", comment = c(ORCID = \"0000-0002-0837-8281\")),\nperson(given = \"Jeremy\", family= \"Magnanensi\", role = c(\"aut\"), email = \"jeremy.magnanensi@gmail.com\"),\nperson(given = \"Myriam\", family= \"Maumy-Bertrand\", role = c(\"aut\"), email = \"myriam.maumy@ehesp.fr\", comment = c(ORCID = \"0000-0002-4615-1512\")))",
  "Author": "Frederic Bertrand [cre, aut]\n(<https://orcid.org/0000-0002-0837-8281>), Jeremy Magnanensi\n[aut], Myriam Maumy-Bertrand [aut]\n(<https://orcid.org/0000-0002-4615-1512>)",
  "Maintainer": "Frederic Bertrand <frederic.bertrand@lecnam.net>",
  "Description": "Several implementations of non-parametric stable\nbootstrap-based techniques to determine the numbers of\ncomponents for Partial Least Squares linear or generalized\nlinear regression models as well as and sparse Partial Least\nSquares linear or generalized linear regression models. The\npackage collects techniques that were published in a book\nchapter (Magnanensi et al. 2016, 'The Multiple Facets of\nPartial Least Squares and Related Methods',\n<doi:10.1007/978-3-319-40643-5_18>) and two articles\n(Magnanensi et al. 2017, 'Statistics and Computing',\n<doi:10.1007/s11222-016-9651-4>) and (Magnanensi et al. 2021,\n'Frontiers in Applied Mathematics and Statistics',\n<doi:10.3389/fams.2021.693126>).",
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