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https://github.com/mmyros/bayes-window/actions/workflows/pytest.yaml/badge.svg\n        :target: https://github.com/mmyros/bayes-window/actions/workflows/pytest.yaml/badge.svg\n\n.. image:: https://readthedocs.org/projects/bayes-window/badge/?version=latest\n        :target: https://bayes-window.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n\n.. image:: https://codecov.io/gh/mmyros/bayes-window/branch/master/graph/badge.svg?token=CQMHJRNC9I\n      :target: https://codecov.io/gh/mmyros/bayes-window\n\n.. image:: https://img.shields.io/lgtm/grade/python/g/mmyros/bayes-window.svg?logo=lgtm\u0026logoWidth=18\n      :target: https://lgtm.com/projects/g/mmyros/bayes-window/context:python\n      :alt: Language grade: Python\n\n============\nBayes Window\n============\n\n.. image:: bw_logo_drawing.png\n   :height: 160\n   :align: center\n\n\nPretty and easy hierarchical Bayesian or linear mixed effects estimation with data overlay\n\n\n* Free software: MIT license\n* Documentation: https://mmyros.github.io/bayes-book/index.html\n\n\nINSTALLATION\n------------\nFor gpu:\n```pip install --upgrade \"jax[cuda102]\" -f https://storage.googleapis.com/jax-releases/jax_releases.html```\nor cudaXXX from `nvcc --version`\n\n\nFeatures\n--------\n\nSee extensive examples https://mmyros.github.io/bayes-book/index.html\n\n\n\nTODO\n----\n- Fit checks for LME under plot_diagnostics()\n- Posterior predictive to mimic data plot\n- Less haphazard testing\n- Shrinkage layer: Should be as easy as alt.layer with unpooled model\n- Prior predictive and posterior predictive plots\n- wait for resolution to https://github.com/vega/vega-lite/issues/4373#issuecomment-447726094\n- Random-effect plots (eg intercepts): bw.plot_extras?\n- Decide on Vega 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