Assumptions: Test how to best introduce warnings / guides

[this-is-sofia]

Example: The RKI data in the project is not i.i.d. (independent and identically distributed) because PLZs that lie close together are highly correlated. Therefore, the results of the PC algorithm can be highly biased.

Test how to best integrate this information. Ideas:

• Use available tests for assumptions (e.g. if they are i.i.d. or stationary) and through warnings
• Suggest algorithms that do need the violated assumption if available
• If no algorithm is available: offer different heuristics to account for the assumption violation but indicate that the results are not reliable anymore. This could intuitively be done by showing outputs of different heuristics and documenting their weaknesses as well as robustness tests whenever possible.