hanzy1110 / BayesianModelSelection

Bayesian model selection for

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BayesianModelSelection

Bayesian model selection for Oxidation Kinetics modelling \ Install requirements in a python enviroment using pip install -r requirements.txt

Milestones completed: 6/2/2022

  • Implemented Inference for diferent models
  • Posterior Predictive plots for every model
  • Results in the IPython Notebook!
  • Compute BIC and logLikelihood for every model
  • Estimate ELPD using WAIC and compare each model
  • Extend the analysis to the whole dataset \ --19/2/2022
  • Added Paralinear model to the model selection framework (taken from Paralinear Oxidation of Cr-Si-C-Coated C/SiC at 1300�C in Wet and Dry Air Environments WU2019)
  • Spline regression implemented (https://docs.pymc.io/projects/examples/en/latest/splines/spline.html)
  • Added spline regression to the model selection framework
  • Data sanitation/normalizing done!

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Bayesian model selection for

License:MIT License


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