<?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>Adaptive Bayesian Graphical Lasso</dc:title>
  <dc:title>R package abglasso version 0.1.1</dc:title>
  <dc:subject>CRAN Task View: Bayesian (https://CRAN.R-project.org/view=Bayesian)</dc:subject>
  <dc:description>Implements a Bayesian adaptive graphical lasso data-augmented block Gibbs sampler. The sampler simulates the posterior distribution of precision matrices of a Gaussian Graphical Model. This sampler was adapted from the original MATLAB routine proposed in Wang (2012) &lt;doi:10.1214/12-BA729&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: MASS, pracma, stats, statmod</dc:relation>
  <dc:relation>Suggests: testthat</dc:relation>
  <dc:creator>Jarod Smith &lt;jarodsmith706@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Jarod Smith [aut, cre] (ORCID: &lt;https://orcid.org/0000-0003-4235-6147&gt;),
  Mohammad Arashi [aut] (ORCID: &lt;https://orcid.org/0000-0003-4793-5674&gt;),
  Andriette Bekker [aut] (ORCID: &lt;https://orcid.org/0000-0002-5881-9241&gt;)</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2021-07-13</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=abglasso</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.abglasso</dc:identifier>
</oai_dc:dc>
