<metapackage xmlns:os="http://opensuse.org/Standards/One_Click_Install" xmlns="http://opensuse.org/Standards/One_Click_Install">
  <group>
    <repositories>
      <repository recommended="true">
        <name>devel:languages:R:autoCRAN</name>
        <summary>Large parts of CRAN (cran.r-project.org) mirrored to OBS in a fully automatic way.</summary>
        <description>This repo contains a large part of CRAN automatically converted to rpm packages.
*ALL* packages in the repo are created and kept uptodate(!) in a fully automatic way using the R package CRAN2OBS (gitlab.com/dsteuer/CRAN2OBS).
At the moment CRAN2OBS is still subject to many changes, but it already works well enough to bring about 15k packages from CRAN to Suse.
If you find packages not working, please contact me. Do not push packages here by hand after manually altering anything in a spec file, please. If you find an important package still missing, send a note, please. May be it is easy to add fitting rules to the scripts. 

Attention: there are Prefer: lines in the project config. Should be rechecked from time to time.</description>
        <url>https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/15.5/</url>
      </repository>
      <repository recommended="true">
        <name>deleted</name>
        <summary>INTERNAL PROJECT</summary>
        <description>don't delete this project, it's used for internal purposes</description>
        <url>https://download.opensuse.org/repositories/deleted/deleted/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Leap:15.5</name>
        <summary></summary>
        <description>openSUSE Leap borrows packages from SLE. The content of the build media is almost the same as Leap:15.2, but the development is drastic different. It includes the binaries (instead of the sources) directly from SLE. https://lists.opensuse.org/opensuse-factory/2020-04/msg00165.html</description>
        <url>https://download.opensuse.org/repositories/openSUSE:/Leap:/15.5/standard/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Backports:SLE-15-SP5</name>
        <summary>Backports project for SLE-15-SP5</summary>
        <description>Backports project for SLE-15-SP5</description>
        <url>https://download.opensuse.org/repositories/openSUSE:/Backports:/SLE-15-SP5/standard/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP5:GA</name>
        <summary></summary>
        <description></description>
        <url>https://download.opensuse.org/repositories/SUSE:/SLE-15-SP5:/GA/pool/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP4:Update</name>
        <summary>SLE 15 SP4</summary>
        <description>SLE 15 SP4</description>
        <url>https://download.opensuse.org/distribution/leap/15.5/repo/oss/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP4:GA</name>
        <summary></summary>
        <description></description>
        <url>https://download.opensuse.org/repositories/SUSE:/SLE-15-SP4:/GA/pool/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP3:Update</name>
        <summary>SLE 15 SP3</summary>
        <description>SLE 15 SP3</description>
        <url>https://download.opensuse.org/distribution/leap/15.5/repo/oss/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP3:GA</name>
        <summary></summary>
        <description></description>
        <url>https://download.opensuse.org/repositories/SUSE:/SLE-15-SP3:/GA/pool/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP2:Update</name>
        <summary>SLE 15 SP2</summary>
        <description>SLE 15 SP2</description>
        <url>https://download.opensuse.org/distribution/leap/15.5/repo/oss/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP2:GA</name>
        <summary>SLE 15 SP2</summary>
        <description>SLE 15 SP2</description>
        <url>https://download.opensuse.org/repositories/SUSE:/SLE-15-SP2:/GA/pool/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP1:Update</name>
        <summary>SLE 15 SP1</summary>
        <description>SLE 15 SP1</description>
        <url>https://download.opensuse.org/distribution/leap/15.5/repo/oss/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15-SP1:GA</name>
        <summary>SLE 15 SP1</summary>
        <description>SLE 15 SP1</description>
        <url>https://download.opensuse.org/repositories/SUSE:/SLE-15-SP1:/GA/pool/</url>
      </repository>
      <repository recommended="true">
        <name>SUSE:SLE-15:Update</name>
        <summary>SLE 15</summary>
        <description>SLE 15</description>
        <url>https://download.opensuse.org/distribution/leap/15.5/repo/oss/</url>
      </repository>
      <repository recommended="false">
        <name>SUSE:SLE-15:GA</name>
        <summary>SLE 15</summary>
        <description>SLE 15</description>
        <url>https://download.opensuse.org/repositories/SUSE:/SLE-15:/GA/pool/</url>
      </repository>
    </repositories>
    <software>
      <item>
        <name>R-multinomialLogitMix</name>
        <summary>Clustering Multinomial Count Data under the Presence of Covariates</summary>
        <description>Methods for model-based clustering of multinomial counts under the
presence of covariates using mixtures of multinomial logit models, as
implemented in Papastamoulis (2023) &lt;DOI:10.1007/s11634-023-00547-5&gt;.
These models are estimated under a frequentist as well as a Bayesian
setup using the Expectation-Maximization algorithm and Markov chain
Monte Carlo sampling (MCMC), respectively. The (unknown) number of
clusters is selected according to the Integrated Completed Likelihood
criterion (for the frequentist model), and estimating the number of
non-empty components using overfitting mixture models after imposing
suitable sparse prior assumptions on the mixing proportions (in the
Bayesian case), see Rousseau and Mengersen (2011)
&lt;DOI:10.1111/j.1467-9868.2011.00781.x&gt;. In the latter case, various
MCMC chains run in parallel and are allowed to switch states. The final
MCMC output is suitably post-processed in order to undo label switching
using the Equivalence Classes Representatives (ECR) algorithm, as
described in Papastamoulis (2016) &lt;DOI:10.18637/jss.v069.c01&gt;.</description>
      </item>
    </software>
  </group>
</metapackage>
