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<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>Mode Estimation, Even in the Multimodal Case</dc:title>
  <dc:title>R package ModEstM version 0.0.1</dc:title>
  <dc:subject>CRAN Task View: Distributions (https://CRAN.R-project.org/view=Distributions)</dc:subject>
  <dc:description>Function ModEstM() is the only one of this package, it estimates the modes of an empirical univariate distribution. It relies on the stats::density() function, even for input control. Due to very good performance of the density estimation, computation time is not an issue. The multiple modes are handled using dplyr::group_by(). For conditions and rates of convergences, see Eddy (1980) &lt;doi:10.1214/aos/1176345080&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.1)</dc:relation>
  <dc:relation>Imports: dplyr, rlang, stats</dc:relation>
  <dc:creator>Jerome Collet &lt;jeromepcollet@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Jerome Collet [aut, cre]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2022-05-19</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=ModEstM</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.ModEstM</dc:identifier>
</oai_dc:dc>