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using MarkovProcesses
load_model("ER")
test_all = true
load_model("ER")
pm1 = ParametricModel(ER, (:k2, Uniform(2.0, 4.0)))
test_all = test_all && 2.0 <= ER[:k2] <= 4.0 && pm1.df == 1
pm2 = ParametricModel(ER, [:k3,:k2], product_distribution(Uniform.([2.5,6.0], [3.5,7.0])))
test_all = test_all && 2.5 <= ER[:k3] <= 3.5 && 6.0 <= ER[:k2] <= 7.0 && pm2.df == 2
pm3 = ParametricModel(ER, (:k3, Uniform(10.0, 11.0)), (:k2, Uniform(13.0, 14.0)))
test_all = test_all && 10.0 <= ER[:k3] <= 11.0 && 13.0 <= ER[:k2] <= 14.0 && pm3.df == 2