This code uses the PEtab problem (written in the yaml file) to perform MCMC sampling with pyPESTO. Afterwards an ensemble is created, that allows to compute the posterior predictive distribution and therefore the credibility intervals for the model output.

The sampling.py scipt of pyPESTO visulize was adjusted for an improved visualization. The used code was also uploaded.

A Conda environment file (.yml) containing the specific version of Python and installed packages with the according versions, can be used to avoid conflicts between package versions.

SEEK ID: https://fairdomhub.org/data_files/6129?version=2

Filename: Bayesian UQ for experimental data code.zip  Download

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Created: 22nd Jul 2022 at 10:00

Last updated: 9th Dec 2022 at 07:08

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Version 2 (latest) Created 7th Dec 2022 at 17:08 by Sebastian Höpfl

Increased sample size to 200,000 on 4 parallel chains. Increased bounds of parameters to a uniform prior distribution in the interval [0, 100] for parameters A and B and [0,1000] for σ.

Version 1 (earliest) Created 22nd Jul 2022 at 10:00 by Sebastian Höpfl

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