[
  {
    "Package": "A3",
    "Version": "1.0.0",
    "Depends": "R (>= 2.15.0), xtable, pbapply",
    "Suggests": "randomForest, e1071",
    "License": "GPL (>= 2)",
    "NeedsCompilation": "no",
    "Author": "Scott Fortmann-Roe",
    "Date": "2015-08-15",
    "Description": "Supplies tools for tabulating and analyzing the results of predictive models. The methods employed are applicable to virtually any predictive model and make comparisons between different methodologies straightforward.",
    "Maintainer": "Scott Fortmann-Roe <scottfr@berkeley.edu>",
    "Packaged": "2015-08-16 14:17:33 UTC; scott",
    "Title": "Accurate, Adaptable, and Accessible Error Metrics for Predictive\nModels",
    "Type": "Package",
    "Published": "2015-08-16",
    "MD5sum.1": "027ebdd8affce8f0effaecfcd5f5ade2"
  },
  {
    "Package": "abbyyR",
    "Version": "0.5.4",
    "Depends": "R (>= 3.2.0)",
    "Imports": "httr, XML, curl, readr, plyr, progress",
    "Suggests": "testthat, rmarkdown, knitr (>= 1.11), lintr",
    "License": "MIT + file LICENSE",
    "NeedsCompilation": "no",
    "Author": "Gaurav Sood [aut, cre]",
    "Authors@R": "person(\"Gaurav\", \"Sood\", email = \"gsood07@gmail.com\", role = c(\"aut\", \"cre\"))",
    "BugReports": "http://github.com/soodoku/abbyyR/issues",
    "Description": "Get text from images of text using Abbyy Cloud Optical Character\n    Recognition (OCR) API. Easily OCR images, barcodes, forms, documents with\n    machine readable zones, e.g. passports. Get the results in a variety of formats\n    including plain text and XML. To learn more about the Abbyy OCR API, see \n    <http://ocrsdk.com/>.",
    "LazyData": "true",
    "Maintainer": "Gaurav Sood <gsood07@gmail.com>",
    "Packaged": "2018-05-30 12:47:37 UTC; soodoku",
    "Title": "Access to Abbyy Optical Character Recognition (OCR) API",
    "URL": "http://github.com/soodoku/abbyyR",
    "VignetteBuilder": "knitr",
    "Published": "2018-05-30",
    "MD5sum.1": "e943e1cc292b17b3e42885976fef9412"
  },
  {
    "Package": "abc",
    "Version": "2.1",
    "Depends": "R (>= 2.10), abc.data, nnet, quantreg, MASS, locfit",
    "License": "GPL (>= 3)",
    "NeedsCompilation": "no",
    "Author": "Csillery Katalin [aut],\n  Lemaire Louisiane [aut],\n  Francois Olivier [aut],\n  Blum Michael [aut, cre]",
    "Authors@R": "c( \n    person(\"Csillery\", \"Katalin\", role = \"aut\", email=\"kati.csillery@gmail.com\"),\n    person(\"Lemaire\", \"Louisiane\", role = \"aut\"),\n    person(\"Francois\", \"Olivier\", role = \"aut\"),\n    person(\"Blum\", \"Michael\",\n    email = \"michael.blum@imag.fr\", role = c(\"aut\", \"cre\")))",
    "Date": "2015-05-04",
    "Description": "Implements several ABC algorithms for\n        performing parameter estimation, model selection, and goodness-of-fit.\n        Cross-validation tools are also available for measuring the\n        accuracy of ABC estimates, and to calculate the\n        misclassification probabilities of different models.",
    "Maintainer": "Blum Michael <michael.blum@imag.fr>",
    "Packaged": "2015-05-05 08:35:25 UTC; mblum",
    "Title": "Tools for Approximate Bayesian Computation (ABC)",
    "Type": "Package",
    "Published": "2015-05-05",
    "Reverse depends": "abctools, EasyABC",
    "Reverse imports": "ecolottery",
    "Reverse suggests": "coala",
    "MD5sum.1": "c9fffe4334c178917f762735aba59653"
  },
  {
    "Package": "abc.data",
    "Version": "1.0",
    "Depends": "R (>= 2.10)",
    "License": "GPL (>= 3)",
    "NeedsCompilation": "no",
    "Author": "Csillery Katalin [aut],\n  Lemaire Louisiane [aut],\n  Francois Olivier [aut],\n  Blum Michael [aut, cre]",
    "Authors@R": "c( \n    person(\"Csillery\", \"Katalin\", role = \"aut\", email=\"kati.csillery@gmail.com\"),\n    person(\"Lemaire\", \"Louisiane\", role = \"aut\"),\n    person(\"Francois\", \"Olivier\", role = \"aut\"),\n    person(\"Blum\", \"Michael\",\n    email = \"michael.blum@imag.fr\", role = c(\"aut\", \"cre\")))",
    "Date": "2015-05-04",
    "Description": "Contains data which are used by functions of the 'abc' package.",
    "Maintainer": "Blum Michael <michael.blum@imag.fr>",
    "Packaged": "2015-05-05 09:25:25 UTC; mblum",
    "Title": "Data Only: Tools for Approximate Bayesian Computation (ABC)",
    "Type": "Package",
    "Published": "2015-05-05",
    "Reverse depends": "abc",
    "Reverse suggests": "abctools",
    "MD5sum.1": "799079dbbdd0cfc9d9c61c3e35241806"
  },
  {
    "Package": "ABC.RAP",
    "Version": "0.9.0",
    "Depends": "R (>= 3.1.0)",
    "Imports": "graphics, stats, utils",
    "Suggests": "knitr, rmarkdown",
    "License": "GPL-3",
    "NeedsCompilation": "no",
    "Author": "Abdulmonem Alsaleh [cre, aut], Robert Weeks [aut], Ian Morison [aut], RStudio [ctb]",
    "Contact": "Ian Morison <ian.morison@otago.ac.nz>",
    "Description": "It aims to identify candidate genes that are “differentially\n    methylated” between cases and controls. It applies Student’s t-test and delta beta analysis to\n    identify candidate genes containing multiple “CpG sites”.",
    "Encoding": "UTF-8",
    "Maintainer": "Abdulmonem Alsaleh <a.alsaleh@hotmail.co.nz>",
    "Packaged": "2016-10-20 01:50:08 UTC; abdul",
    "SystemRequirements": "GNU make",
    "Title": "Array Based CpG Region Analysis Pipeline",
    "VignetteBuilder": "knitr",
    "Published": "2016-10-20",
    "MD5sum.1": "38c65a7251d28ef2462ee430ded95700"
  }
]