- need ci for RQ
- enveloping the groud truth (parameter or test)
- My talk and slide on BayesWF with the following abstract:
- "what" problems to solve and "how" to solve with one's and community's resources.
- This would help you to classify the concepts on model misspecification, coding error, inaccurate computation.
- I am particularly interested in simulation-based calibration where the as a whole is tested and updated based on the simulated parameters' posterior coverage.
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- Starting with the diagram `Customize variability and target testing` with further explanation [here](https://github.com/hyunjimoon/SBC/wiki/Customize-variability-and-target-testing)
![[Pasted image 20220821194432.png]]
- explain how each source of uncertainty can be formulated in Bayesian experiment for the model checking and expansion.