<?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>A Bayesian Semiparametric Approach to Correlated ROC Surfaces</dc:title>
  <dc:title>R package sorocs version 0.1.0</dc:title>
  <dc:description>A Bayesian semiparametric Dirichlet process mixtures to estimate correlated receiver operating characteristic (ROC) surfaces and the associated volume under the surface (VUS) with stochastic order constraints. The reference paper is:Zhen Chen, Beom Seuk Hwang, (2018) "A Bayesian semiparametric approach to correlated ROC surfaces with stochastic order constraints". Biometrics, 75, 539-550. &lt;doi:10.1111/biom.12997&gt;. </dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: MASS, MCMCpack, mvtnorm</dc:relation>
  <dc:relation>Suggests: knitr, rmarkdown</dc:relation>
  <dc:creator>Weimin Zhang &lt;zhangwm@hotmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Zhen Chen [aut],
  Beom Seuk Hwang [aut],
  Weimin Zhang [cre]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2020-03-13</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=sorocs</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.sorocs</dc:identifier>
</oai_dc:dc>