<metapackage xmlns:os="http://opensuse.org/Standards/One_Click_Install" xmlns="http://opensuse.org/Standards/One_Click_Install">
  <group distversion="openSUSE Tumbleweed">
    <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/openSUSE_Tumbleweed/</url>
      </repository>
      <repository recommended="true">
        <name>devel:languages:R:autoCRANsupp</name>
        <summary>Supplements for the autoCRAN project</summary>
        <description>autoCRANsupp contains *only* 
- libraries needed to build a worthy number of R packages that are not in factory/tumbleweed, i.e. udunits2-1 
- a link to d:l:R:released/R-base to provide newer versions for older SuSE releases. A lot of packages need the latest R.

This project will be as small as possible. 
In a best case scenario only R-base will remain here to be included for building autoCRAN.

</description>
        <url>https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRANsupp/openSUSE_Tumbleweed/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Factory</name>
        <summary>The next openSUSE distribution</summary>
        <description>openSUSE Tumbleweed: The Bleeding Edge, Perfected.
Tumbleweed is the ultimate rolling release distribution, providing the latest software as it’s released, built upon a foundation of world-class stability and testing.

* Always Current: Get the newest kernel, IDEs, desktops, and applications automatically.

* Powerfully Stable: Experience the velocity of a rolling release without sacrificing the reliability you depend on.

* Engineered for Professionals: The top choice for Developers, Power Users, and openSUSE Contributors who need the best tools for the job.

If you demand the latest stable software, your choice is Tumbleweed.

Staging dashboard is located at: https://build.opensuse.org/staging_workflows/openSUSE:Factory 

List of known devel projects: https://build.opensuse.org/package/view_file/openSUSE:Factory:Staging/dashboard/devel_projects

Have a look at http://en.opensuse.org/Portal:Factory for more details.</description>
        <url>https://download.opensuse.org/tumbleweed/repo/oss/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Tumbleweed</name>
        <summary>Tumbleweed</summary>
        <description>Tumbleweed is the openSUSE Rolling Release

This OBS Project represents the content of the currently published
snapshot. The newer repository for next publish can be found in openSUSE:Factory standard repository.
</description>
        <url>https://download.opensuse.org/repositories/openSUSE:/Tumbleweed/standard/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Tumbleweed</name>
        <summary>Tumbleweed</summary>
        <description>Tumbleweed is the openSUSE Rolling Release

This OBS Project represents the content of the currently published
snapshot. The newer repository for next publish can be found in openSUSE:Factory standard repository.
</description>
        <url>https://download.opensuse.org/tumbleweed/repo/oss/</url>
      </repository>
      <repository recommended="false">
        <name>openSUSE:Factory</name>
        <summary>The next openSUSE distribution</summary>
        <description>openSUSE Tumbleweed: The Bleeding Edge, Perfected.
Tumbleweed is the ultimate rolling release distribution, providing the latest software as it’s released, built upon a foundation of world-class stability and testing.

* Always Current: Get the newest kernel, IDEs, desktops, and applications automatically.

* Powerfully Stable: Experience the velocity of a rolling release without sacrificing the reliability you depend on.

* Engineered for Professionals: The top choice for Developers, Power Users, and openSUSE Contributors who need the best tools for the job.

If you demand the latest stable software, your choice is Tumbleweed.

Staging dashboard is located at: https://build.opensuse.org/staging_workflows/openSUSE:Factory 

List of known devel projects: https://build.opensuse.org/package/view_file/openSUSE:Factory:Staging/dashboard/devel_projects

Have a look at http://en.opensuse.org/Portal:Factory for more details.</description>
        <url>https://download.opensuse.org/repositories/openSUSE:/Factory/ports/</url>
      </repository>
    </repositories>
    <software>
      <item>
        <name>R-exametrika</name>
        <summary>Test Theory Analysis and Biclustering</summary>
        <description>Implements comprehensive test data engineering methods as described in
Shojima (2022, ISBN:978-9811699856). Provides statistical techniques
for engineering and processing test data: Classical Test Theory (CTT)
with reliability coefficients for continuous ability assessment; Item
Response Theory (IRT) including Rasch, 2PL, and 3PL models with
item/test information functions; Latent Class Analysis (LCA) for
nominal clustering; Latent Rank Analysis (LRA) for ordinal clustering
with automatic determination of cluster numbers; Biclustering methods
including infinite relational models for simultaneous clustering of
examinees and items without predefined cluster numbers; and Bayesian
Network Models (BNM) for visualizing inter-item dependencies. Features
local dependence analysis through LRA and biclustering, parameter
estimation, dimensionality assessment, and network structure
visualization for educational, psychological, and social science
research.</description>
      </item>
    </software>
  </group>
</metapackage>
