<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-LambertW</name>
        <summary>Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data</summary>
        <description>Lambert W x F distributions are a generalized framework to analyze
skewed, heavy-tailed data. It is based on an input/output system, where
the output random variable (RV) Y is a non-linearly transformed version
of an input RV X ~ F with similar properties as X, but slightly skewed
(heavy-tailed). The transformed RV Y has a Lambert W x F distribution.
This package contains functions to model and analyze skewed,
heavy-tailed data the Lambert Way: simulate random samples, estimate
parameters, compute quantiles, and plot/ print results nicely. The most
useful function is 'Gaussianize', which works similarly to 'scale', but
actually makes the data Gaussian. A do-it-yourself toolkit allows users
to define their own Lambert W x 'MyFavoriteDistribution' and use it in
their analysis right away.</description>
      </item>
    </software>
  </group>
</metapackage>
