<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Compare Big Datasets to the Uniform Distribution</dc:title>
  <dc:title>R package ggQQunif version 0.1.5</dc:title>
  <dc:description>A quantile-quantile plot can be used to compare a sample of p-values 
  to the uniform distribution.  But when the dataset is big (i.e. &gt; 1e4 p-values),
  plotting the quantile-quantile plot can be slow.  geom_QQ uses all the data to
  calculate the quantiles, but thins it out in a way that focuses on points near zero 
  before plotting to speed up plotting and decrease file size, when vector graphics are stored.  </dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: scales, ggplot2, dplyr</dc:relation>
  <dc:creator>Robert Corty &lt;rcorty@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Robert Corty [aut, cre]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2018-03-14</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=ggQQunif</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.ggQQunif</dc:identifier>
</oai_dc:dc>
