<?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>Package Admix for Admixture (aka Contamination) Models</dc:title>
  <dc:title>R package admix version 2.6.1</dc:title>
  <dc:description>Implements techniques to estimate the unknown quantities
    related to two-component admixture models, where the two components
    can belong to any distribution (note that in the case of multinomial
    mixtures, the two components must belong to the same family).
    Estimation methods depend on the assumptions made on the unknown
    component density; see Bordes and Vandekerkhove (2010)
    &lt;doi:10.3103/S1066530710010023&gt;, Patra and Sen (2016)
    &lt;doi:10.1111/rssb.12148&gt;, and Milhaud, Pommeret, Salhi, Vandekerkhove
    (2024) &lt;doi:10.3150/23-BEJ1593&gt;. In practice, one can estimate both
    the mixture weight and the unknown component density in a wide variety
    of frameworks. On top of that, hypothesis tests can be performed in
    one and two-sample contexts to test the unknown component density (see
    Milhaud, Pommeret, Salhi and Vandekerkhove (2022)
    &lt;doi:10.1016/j.jspi.2021.05.010&gt;, and Milhaud, Pommeret, Salhi,
    Vandekerkhove (2024) &lt;doi:10.3150/23-BEJ1593&gt;). Finally, clustering of
    unknown mixture components is also feasible in a K-sample setting (see
    Milhaud, Pommeret, Salhi, Vandekerkhove (2024) 
    &lt;https://jmlr.org/papers/v25/23-0914.html&gt;).</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 2.10)</dc:relation>
  <dc:relation>Imports: base, cubature, fdrtool, graphics, Iso, MASS, orthopolynom,
pracma, Rcpp, Rdpack, stats, utils</dc:relation>
  <dc:relation>LinkingTo: Rcpp</dc:relation>
  <dc:relation>Suggests: doParallel, doRNG, evd, flexsurv, foreach, gridExtra, knitr,
lattice, logitnorm, plyr, reshape2, rmarkdown, rmutil, mockery,
testthat (&gt;= 3.0.0)</dc:relation>
  <dc:creator>Xavier Milhaud &lt;xavier.milhaud.research@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Xavier Milhaud [aut, cre],
  Pierre Vandekerkhove [ctb],
  Denys Pommeret [ctb],
  Yahia Salhi [ctb]</dc:contributor>
  <dc:rights>GPL (&gt;= 3)</dc:rights>
  <dc:date>2026-05-30</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=admix</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.admix</dc:identifier>
</oai_dc:dc>
