Sofia Faltenbacher

check why. ``` def test_second_toy_model_example(self): rdnv = self.seeded_random.normalvariate model = IIDSampleGenerator( edges=[ SampleEdge(NodeReference("A"), NodeReference("C"), 1), SampleEdge(NodeReference("B"), NodeReference("C"), 2), SampleEdge(NodeReference("A"), NodeReference("D"), 3), SampleEdge(NodeReference("B"), NodeReference("D"), 1), SampleEdge(NodeReference("C"), NodeReference("D"), 1), SampleEdge(NodeReference("B"), NodeReference("E"), 4),...

Fix Time Series Data Generator: Add initial values drawn from distribution

1

Use analytic results for mean and variance (such that the process stays stationary) and normal distribution

Implement strategies for interpolation of missing data points on the graph.

Think of an example that runs into the situations in the pictures and test if the current quadruple orientation rules work as they are supposed to also in bigger examples....

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...

Currently, the graph is initialised with one hard coded skeleton (create_all_possible_edges). This should be configurable such that including prior knowledge becomes easy. Also, when initialising the pre-configured algorithms, you should...

At the moment, multiple edges can end at the same point of a node and therefore it can be hard to differentiate which end belongs to which edge. This can...

Currently, we implemented causal effect estimation which is guaranteed to be unbiased (and even variance minimizing) for directed acyclic graphs (DAGs): regressing on all parents. However, this does not work...