{
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  "Package": "cosso",
  "Version": "2.1-2",
  "Date": "2023-03-07",
  "Title": "Fit Regularized Nonparametric Regression Models Using COSSO\nPenalty",
  "Authors@R": "c(\nperson(\"Hao Helen\", \"Zhang\", email = \"hzhang@math.arizona.edu\",\nrole = c(\"aut\", \"cph\")),\nperson(\"Chen-Yen\", \"Lin\", email = \"clin5@ncsu.edu\",\nrole = c(\"aut\", \"cph\")),\nperson(\"Isaac\", \"Ray\", email = \"null@stat.tamu.edu\",\nrole = c(\"cre\", \"ctb\"))\n)",
  "Description": "The COSSO regularization method automatically estimates\nand selects important function components by a\nsoft-thresholding penalty in the context of smoothing spline\nANOVA models. Implemented models include mean regression,\nquantile regression, logistic regression and the Cox regression\nmodels.",
  "License": "GPL (>= 2)",
  "NeedsCompilation": "no",
  "URL": "https://arxiv.org/abs/math/0702659",
  "Packaged": {
    "Date": "2026-05-27 08:43:06 UTC",
    "User": "root"
  },
  "Author": "Hao Helen Zhang [aut, cph], Chen-Yen Lin [aut, cph], Isaac Ray\n[cre, ctb]",
  "Maintainer": "Isaac Ray <null@stat.tamu.edu>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2023-03-08 08:30:09 UTC",
  "RemoteUrl": "https://github.com/cran/cosso",
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    "message": "version 2.1-2\n",
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  "_userbio": {
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    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/cosso"
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  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/cosso.html",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "manual.pdf"
  ],
  "_realowner": "cran",
  "_cranurl": false,
  "_releases": [
    {
      "version": "1.0-1",
      "date": "2010-12-13"
    },
    {
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      "date": "2012-05-04"
    },
    {
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      "date": "2013-03-11"
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      "date": "2023-03-08"
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    "ACV.lambda",
    "bigGram",
    "cosso",
    "cosso.Binomial",
    "cosso.Cox",
    "cosso.Cox.Parallel",
    "cosso.Cox.Sequential",
    "cosso.Gaussian",
    "cosso.qr",
    "cosso.qr.Parallel",
    "cosso.qr.Sequential",
    "cvlam.Gaussian",
    "cvlam.logistic",
    "cvsplitID",
    "garrote.Cox",
    "garrote.Logistic",
    "garrote.Logistic.GH",
    "garrote.qr",
    "genK",
    "genK.cat",
    "gradient.Hessian.C",
    "gradient.Hessian.Theta",
    "kqr",
    "My_solve",
    "My_solve.QP",
    "PartialLik",
    "plot.cosso",
    "predict.cosso",
    "rescale",
    "rho",
    "RiskSet",
    "SSANOVAwt",
    "SSANOVAwt.Binomial",
    "SSANOVAwt.Cox",
    "SSANOVAwt.Gaussian",
    "SSANOVAwt.qr",
    "sspline",
    "sspline.Binomial",
    "sspline.Cox",
    "tune.cosso",
    "tune.cosso.Binomial",
    "tune.cosso.Cox",
    "tune.cosso.Gaussian",
    "twostep.Binomial",
    "twostep.Cox",
    "twostep.Gaussian",
    "twostep.qr",
    "wsGram"
  ],
  "_datasets": [
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      "name": "BUPA",
      "title": "BUPA Liver Disorder Data",
      "object": "BUPA",
      "file": "BUPA.RData",
      "class": [
        "data.frame"
      ],
      "fields": [
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        "MCV",
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        "SGPT",
        "SGOT",
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        "DRINKS"
      ],
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      "class": [
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        "hum",
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        "wind"
      ],
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      "table": true,
      "tojson": true
    },
    {
      "name": "veteran",
      "title": "Veterans' Administration Lung Cancer study",
      "object": "veteran",
      "file": "veteran.RData",
      "class": [
        "data.frame"
      ],
      "fields": [
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        "status",
        "trt",
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        "diagtime",
        "age",
        "prior"
      ],
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  "_help": [
    {
      "page": "BUPA",
      "title": "BUPA Liver Disorder Data",
      "topics": [
        "BUPA"
      ]
    },
    {
      "page": "cosso",
      "title": "Fit a generalized nonparametric model with cosso penalty",
      "topics": [
        "cosso"
      ]
    },
    {
      "page": "ozone",
      "title": "Ozone pollution data in Los Angels, 1976",
      "topics": [
        "ozone"
      ]
    },
    {
      "page": "plot.cosso",
      "title": "Plot method for COSSO object",
      "topics": [
        "plot.cosso"
      ]
    },
    {
      "page": "predict.cosso",
      "title": "Make predictions or extract coefficients from a cosso model",
      "topics": [
        "predict.cosso"
      ]
    },
    {
      "page": "SSANOVAwt",
      "title": "Compute adaptive weights by fitting a SS-ANOVA model",
      "topics": [
        "SSANOVAwt"
      ]
    },
    {
      "page": "tune.cosso",
      "title": "Tuning procedure for cosso",
      "topics": [
        "tune.cosso"
      ]
    },
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      "title": "Veterans' Administration Lung Cancer study",
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