<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-hybridts</name>
        <summary>Hybrid Time Series Forecasting Using Error Remodeling Approach</summary>
        <description>Method and tool for generating hybrid time series forecasts using an
error remodeling approach. These forecasting approaches utilize a
recursive technique for modeling the linearity of the series using a
linear method (e.g., ARIMA, Theta, etc.) and then models (forecasts)
the residuals of the linear forecaster using non-linear neural networks
(e.g., ANN, ARNN, etc.). The hybrid architectures comprise three steps:
firstly, the linear patterns of the series are forecasted which are
followed by an error re-modeling step, and finally, the forecasts from
both the steps are combined to produce the final output. This method
additionally provides the confidence intervals as needed. Ten different
models can be implemented using this package. This package generates
different types of hybrid error correction models for time series
forecasting based on the algorithms by Zhang. (2003), Chakraborty et
al. (2019), Chakraborty et al. (2020), Bhattacharyya et al. (2021),
Chakraborty et al. (2022), and Bhattacharyya et al. (2022)
&lt;doi:10.1016/S0925-2312(01)00702-0&gt; &lt;doi:10.1016/j.physa.2019.121266&gt;
&lt;doi:10.1016/j.chaos.2020.109850&gt; &lt;doi:10.1109/IJCNN52387.2021.9533747&gt;
&lt;doi:10.1007/978-3-030-72834-2_29&gt; &lt;doi:10.1007/s11071-021-07099-3&gt;.</description>
      </item>
    </software>
  </group>
</metapackage>
