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You can use ProbabilityDistribution to define your own probability distribution from a CDF: dist = ProbabilityDistribution[{"CDF", 1/2 Erfc[(0.1 - x)/(Sqrt[2] 1.2)]}, {x, -∞, ∞}] With some data data = RandomVariate[NormalDistribution[], 50]; you can now perform KolmogorovSmirnovTest[data, dist]


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There is a undocumented input form such as: DegreeGraphDistribution[indegree, outdegree] For example: g = RandomGraph[ DegreeGraphDistribution[{1, 3, 3, 1, 2}, {3, 1, 3, 2, 1}]]; VertexInDegree[g] {1, 3, 3, 1, 2} VertexOutDegree[g] {3, 1, 3, 2, 1}



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