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Merge pull request #257 from DoubleML/dev
Update Documentation for 0.11.0
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.devcontainer/Dockerfile.dev

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@@ -62,7 +62,7 @@ COPY --chown=$USERNAME:$USERNAME requirements.txt /tmp/requirements.txt
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RUN python -m venv /home/$USERNAME/.venv && \
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/home/$USERNAME/.venv/bin/python -m pip install --upgrade pip && \
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/home/$USERNAME/.venv/bin/pip install --no-cache-dir -r /tmp/requirements.txt && \
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/home/$USERNAME/.venv/bin/pip install --no-cache-dir git+https://github.com/DoubleML/doubleml-for-py.git@main#egg=DoubleML[rdd]
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/home/$USERNAME/.venv/bin/pip install --no-cache-dir "DoubleML[rdd] @ git+https://github.com/DoubleML/doubleml-for-py.git@main"
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# Set the virtual environment as the default Python environment
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ENV PATH="/home/$USERNAME/.venv/bin:$PATH"

doc/api/data_class.rst

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DoubleMLData
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DoubleMLClusterData
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DoubleMLPanelData
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DoubleMLSSMData
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DoubleMLRDDData
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DoubleMLDIDData

doc/api/datasets.rst

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Dataset Loaders
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~~~~~~~~~~~~~~~
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.. currentmodule:: doubleml
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.. currentmodule:: doubleml.datasets
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.. autosummary::
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:toctree: generated/
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datasets.fetch_401K
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datasets.fetch_bonus
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fetch_401K
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fetch_bonus
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Dataset Generators
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~~~~~~~~~~~~~~~~~~
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.. autosummary::
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:toctree: generated/
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datasets.make_plr_CCDDHNR2018
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datasets.make_pliv_CHS2015
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datasets.make_irm_data
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datasets.make_iivm_data
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datasets.make_plr_turrell2018
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datasets.make_pliv_multiway_cluster_CKMS2021
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datasets.make_ssm_data
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datasets.make_confounded_plr_data
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datasets.make_confounded_irm_data
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datasets.make_heterogeneous_data
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datasets.make_irm_data_discrete_treatments
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irm.datasets.make_irm_data
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irm.datasets.make_iivm_data
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irm.datasets.make_heterogeneous_data
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irm.datasets.make_irm_data_discrete_treatments
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irm.datasets.make_confounded_irm_data
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irm.datasets.make_ssm_data
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plm.datasets.make_plr_CCDDHNR2018
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plm.datasets.make_plr_turrell2018
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plm.datasets.make_lplr_LZZ2020
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plm.datasets.make_pliv_CHS2015
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plm.datasets.make_pliv_multiway_cluster_CKMS2021
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plm.datasets.make_confounded_plr_data
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did.datasets.make_did_SZ2020
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did.datasets.make_did_CS2021
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rdd.datasets.make_simple_rdd_data
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did.datasets.make_did_cs_CS2021
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rdd.datasets.make_simple_rdd_data

doc/api/dml_models.rst

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:template: class.rst
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DoubleMLPLR
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DoubleMLLPLR
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DoubleMLPLIV
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doc/api/utility.rst

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utils.DoubleMLPolicyTree
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utils.GlobalRegressor
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utils.GlobalClassifier
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utils.PSProcessorConfig
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utils.PSProcessor
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Utility Functions
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~~~~~~~~~~~~~~~~~

doc/conf.py

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"navbar_align": "left",
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"logo": {
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"text": project,
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"image_light": "img/logo.png",
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"image_dark": "img/logo_dark.png",
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"image_light": "../img/logo.png",
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"image_dark": "../img/logo_dark.png",
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},
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"header_links_before_dropdown": 6,
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"use_edit_page_button": True,
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html_favicon = "../img/favicon.ico"
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html_sidebars = {
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"**": [
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"logo.html",
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"search-field.html",
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"https://doi.org/10.1097%2FEDE.0b013e3181f74493",
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# Valid DOI; Causes 403 Client Error: Forbidden for url:...
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"https://doi.org/10.3982/ECTA15732",
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# Valid DOI; Causes 403 Client Error: Forbidden for url:...
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"https://doi.org/10.1093/ectj/utab019"
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]
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# To execute R code via jupyter-execute one needs to install the R kernel for jupyter

doc/examples/did/py_did.ipynb

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doc/examples/did/py_did_pretest.ipynb

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doc/examples/did/py_panel.ipynb

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"metadata": {},
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"outputs": [],
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"source": [
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"np.random.seed(42)\n",
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"dml_obj = DoubleMLDIDMulti(dml_data, **default_args)\n",
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"dml_obj.fit()\n",
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"print(dml_obj)"

doc/examples/did/py_panel_simple.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Event Study Aggregation\n",
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"### Event Study Aggregation\n",
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"\n",
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"Finally, `aggregation=\"eventstudy\"` aggregates $\\widehat{ATT}(\\mathrm{g},t_\\text{pre},t_\\text{eval})$ based on exposure time $e = t_\\text{eval} - \\mathrm{g}$ (respecting group size)."
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]

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