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  "Type": "Package",
  "Title": "Augmented and Penalized Minimization Method L0",
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  "Date": "2026-06-13",
  "Authors@R": "c(\nperson(\"Xiang\", \"Li\", email = \"spiritcoke@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Shanghong\", \"Xie\", role = \"aut\"),\nperson(\"Donglin\", \"Zeng\", role = \"aut\"),\nperson(\"Yuanjia\", \"Wang\", role = \"aut\"))",
  "Description": "Fit linear, logistic and Cox models regularized with L0,\nlasso (L1), elastic-net (L1 and L2), or net (L1 and Laplacian)\npenalty, and their adaptive forms, such as adaptive lasso /\nelastic-net and net adjusting for signs of linked coefficients.\nIt solves the L0 penalty problem by simultaneously selecting\nregularization parameters and performing hard-thresholding or\nselecting the number of non-zeros. This augmented and penalized\nminimization method provides an approximation solution to the\nL0 penalty problem, but runs as fast as L1 regularization. The\npackage uses a one-step coordinate descent algorithm and runs\nextremely fast by taking into account the sparsity structure of\ncoefficients. It can handle very high dimensional data and has\nsuperior selection performance.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
  "Language": "en-US",
  "URL": "https://github.com/LeeSprite/APML0",
  "BugReports": "https://github.com/LeeSprite/APML0/issues",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-19 18:38:03 UTC",
    "User": "root"
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  "Author": "Xiang Li [aut, cre], Shanghong Xie [aut], Donglin Zeng [aut],\nYuanjia Wang [aut]",
  "Maintainer": "Xiang Li <spiritcoke@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-06-19 18:11:21 UTC",
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