{
  "about": {
    "home": "http://www.jstatsoft.org/v33/i01/.",
    "license": "GPL-2",
    "summary": "Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below. "
  },
  "build": {
    "entry_points": [],
    "features": [],
    "rpaths": [
      "lib/R/lib/",
      "lib/"
    ],
    "script_env": [],
    "string": "",
    "track_features": []
  },
  "package": {
    "name": "r-glmnet",
    "version": "2.0_2"
  },
  "requirements": {
    "build": [
      "r",
      "r-matrix >=1.0_6",
      "r-foreach",
      "gcc"
    ],
    "conflicts": [],
    "run": [
      "r",
      "r-matrix >=1.0_6",
      "r-foreach",
      "libgcc"
    ]
  },
  "source": {
    "fn": "glmnet_2.0-2.tar.gz",
    "git_rev": "",
    "md5": "",
    "patches": [],
    "path": "",
    "svn_rev": "",
    "url": [
      "http://cran.r-project.org/src/contrib/glmnet_2.0-2.tar.gz",
      "http://cran.r-project.org/src/contrib/Archive/glmnet/glmnet_2.0-2.tar.gz"
    ]
  },
  "test": {
    "commands": [
      "$R -e \"library('glmnet')\""
    ],
    "files": [],
    "imports": [],
    "requires": []
  }
}