Many models have parameters that are difficult or impossible to measure. In the case of a curvefit or regression, we are trying to determine parameters that make the model fit the data. In other cases, we have an estimate of a parameter, but we wish to use observed data to improve our estimate. This tool has examples illustrating common uses.

Python and PySide

Researchers should cite this work as follows:

• Martin Hunt, Benjamin P Haley, Jan Ebinger, Alejandro Strachan (2015), "Bayesian Calibration," https://nanohub.org/resources/bayes. (DOI: 10.4231/D3H12V838).

  BibTex | EndNote

1. Bayesian
2. Bayesian calibration
3. NCN Group - Materials Science
4. python
5. regression
6. uncertainty quantification (UQ)