{
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  "Package": "apca",
  "Type": "Package",
  "Title": "Advanced Principal Component Analysis",
  "Version": "1.0.0",
  "Date": "2026-04-19",
  "Authors@R": "c(\nperson(given = \"Angga Dwi\", family = \"Mulyanto\", role = c(\"aut\", \"cre\"), email = \"angga.dwi.m@gmail.com\", comment = \"Institut Teknologi Sepuluh Nopember, Universitas Islam Negeri Maulana Malik Ibrahim Malang\"),\nperson(given = \"Bambang Widjanarko\", family = \"Otok\", role = \"aut\", comment = \"Institut Teknologi Sepuluh Nopember\"),\nperson(given = \"Jerry Dwi Trijoyo\", family = \"Purnomo\", role = \"aut\", comment = \"Institut Teknologi Sepuluh Nopember\")\n)",
  "Description": "Provides nine computational algorithms for dimensionality\nreduction via Principal Component Analysis (PCA), built using\nan object-oriented (S3) architecture. The package includes\nclassical and modern methods: Singular Value Decomposition\n(SVD) based on Eckart and Young (1936)\n<doi:10.1007/BF02288367>, Power Iteration based on Hotelling\n(1933) <doi:10.1037/h0071325>, QR Algorithm based on Francis\n(1961) <doi:10.1093/comjnl/4.3.265>, Jacobi Algorithm based on\nJacobi (1846) <doi:10.1515/crll.1846.30.51>, Arnoldi Iteration\nbased on Arnoldi (1951) <doi:10.1090/qam/42792>, 'NIPALS' based\non Wold (1975) <doi:10.1017/S0021900200047604>, Alternating\nLeast Squares (ALS) based on Kolda and Bader (2009)\n<doi:10.1137/07070111X>, Probabilistic PCA (PPCA) with EM\nAlgorithm based on Tipping and Bishop (1999)\n<doi:10.1111/1467-9868.00196>, and Generalized Hebbian\nAlgorithm (GHA) based on Sanger (1989)\n<doi:10.1016/0893-6080(89)90044-0>.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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    "User": "root"
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  "Author": "Angga Dwi Mulyanto [aut, cre] (Institut Teknologi Sepuluh\nNopember, Universitas Islam Negeri Maulana Malik Ibrahim\nMalang), Bambang Widjanarko Otok [aut] (Institut Teknologi\nSepuluh Nopember), Jerry Dwi Trijoyo Purnomo [aut] (Institut\nTeknologi Sepuluh Nopember)",
  "Maintainer": "Angga Dwi Mulyanto <angga.dwi.m@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-04-28 20:44:52 UTC",
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      "title": "Advanced Principal Component Analysis (APCA)",
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