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Release notes
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=============
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+ .. tabbed :: Python
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+ **DoubleML 0.1.0 **
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+
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+ - Initial release
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+ - Development at `https://github.com/DoubleML/doubleml-for-py <https://github.com/DoubleML/doubleml-for-py >`_
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+ - The Python package **DoubleML ** provides an implementation of the double / debiased machine learning framework of
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+ `Chernozhukov et al. (2018) <https://doi.org/10.1111/ectj.12097) >`_.
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+ - Implements double machine learning for four different models:
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+
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+ - Partially linear regression models (PLR) in class ``DoubleMLPLR ``
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+ - Partially linear IV regression models (PLIV) in class ``DoubleMLPLIV ``
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+ - Interactive regression models (IRM) in class ``DoubleMLIRM ``
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+ - Interactive IV regression models (IIVM) in class ``DoubleMLIIVM ``
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+
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+ - All model classes are inherited from an abstract base class ``DoubleML `` where the key elements of double machine
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+ learning are implemented.
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+
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+ .. tabbed :: R
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+
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+ **DoubleML 0.1.0 **
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+
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+ - Initial release
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+ - Development at `https://github.com/DoubleML/doubleml-for-r <https://github.com/DoubleML/doubleml-for-r >`_
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+ - The R package **DoubleML ** provides an implementation of the double / debiased machine learning framework of
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+ `Chernozhukov et al. (2018) <https://doi.org/10.1111/ectj.12097) >`_.
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+ - Implements double machine learning for four different models:
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+
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+ - Partially linear regression models (PLR) in class ``DoubleMLPLR ``
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+ - Partially linear IV regression models (PLIV) in class ``DoubleMLPLIV ``
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+ - Interactive regression models (IRM) in class ``DoubleMLIRM ``
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+ - Interactive IV regression models (IIVM) in class ``DoubleMLIIVM ``
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+
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+ - All model classes are inherited from ``DoubleML `` where the key elements of double machine learning are
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+ implemented.
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+
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