<?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>Estimation of Large Block Covariance Matrices</dc:title>
  <dc:title>R package BlockCov version 0.1.1</dc:title>
  <dc:description>Computation of large covariance matrices having a block structure up to a permutation of their columns and rows 
    from a small number of samples with respect to the dimension of the matrix.
 The method is described in the paper Perrot-Dockès et al. (2019) &lt;arXiv:1806.10093&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: Matrix, stats, Rdpack, BBmisc, dplyr, tibble, magrittr, rlang</dc:relation>
  <dc:relation>Suggests: knitr</dc:relation>
  <dc:creator>Marie Perrot-Dockès &lt;marie.perrocks@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>M. Perrot-Dock\`es, C. Lévy-Leduc</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2019-04-13</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=BlockCov</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.BlockCov</dc:identifier>
</oai_dc:dc>