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bayes-window's Introduction

Documentation Status https://codecov.io/gh/mmyros/bayes-window/branch/master/graph/badge.svg?token=CQMHJRNC9I Language grade: Python

Bayes Window

bw_logo_drawing.png

Pretty and easy hierarchical Bayesian or linear mixed effects estimation with data overlay

INSTALLATION

For gpu: `pip install --upgrade "jax[cuda102]" -f https://storage.googleapis.com/jax-releases/jax_releases.html` or cudaXXX from nvcc --version

Features

See extensive examples https://mmyros.github.io/bayes-book/index.html

TODO

  • Fit checks for LME under plot_diagnostics()
  • Posterior predictive to mimic data plot
  • Less haphazard testing
  • Shrinkage layer: Should be as easy as alt.layer with unpooled model
  • Prior predictive and posterior predictive plots
  • wait for resolution to vega/vega-lite#4373 (comment)
  • Random-effect plots (eg intercepts): bw.plot_extras?
  • Decide on Vega theme

bayes-window's People

Contributors

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Watchers

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bayes-window's Issues

PPC diagnostics

flatten=[] in arviz to get PPC faceting, or use self.levels

dummy variable

Description

if len(conditions)>1: condition = 'combined condition'. Then, lme should work

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