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left= Normal(mu = 0, sigma = 1)
right= Normal(mu = 0, sigma = 1)
transformation= id_1
inverseTransformation= id_1
----------------------------------------------------------------------------------------------------
left= JointDistribution(Normal(mu = 0, sigma = 1), Gumbel(beta = 1, gamma = 0), IndependentCopula(dimension = 2))
right= JointDistribution(Triangular(a = -1, m = 0, b = 1), Triangular(a = -1, m = 0, b = 1), IndependentCopula(dimension = 2))
transformation= | y0 = Normal(mu = 0, sigma = 1) -> y0 : Triangular(a = -1, m = 0, b = 1)
| y1 = Gumbel(beta = 1, gamma = 0) -> y1 : Triangular(a = -1, m = 0, b = 1)
inverseTransformation= | y0 = Triangular(a = -1, m = 0, b = 1) -> y0 : Normal(mu = 0, sigma = 1)
| y1 = Triangular(a = -1, m = 0, b = 1) -> y1 : Gumbel(beta = 1, gamma = 0)
----------------------------------------------------------------------------------------------------
left= JointDistribution(Normal(mu = 0, sigma = 1), Gumbel(beta = 1, gamma = 0), IndependentCopula(dimension = 2))
right= JointDistribution(Triangular(a = -1, m = 0, b = 1), Triangular(a = -1, m = 0, b = 1), GumbelCopula(theta = 2))
transformation= ((| y0 = Uniform(a = 0, b = 1) -> y0 : Triangular(a = -1, m = 0, b = 1)
| y1 = Uniform(a = 0, b = 1) -> y1 : Triangular(a = -1, m = 0, b = 1)
)o(InverseRosenblattEvaluation(Normal(2)->GumbelCopula(theta = 2))))o(| y0 = [x0]->[x0]
| y1 = Gumbel(beta = 1, gamma = 0) -> y1 : Normal(mu = 0, sigma = 1)
)
inverseTransformation= (| y0 = [x0]->[x0]
| y1 = Normal(mu = 0, sigma = 1) -> y1 : Gumbel(beta = 1, gamma = 0)
)o((RosenblattEvaluation(GumbelCopula(theta = 2)->Normal(2))o(| y0 = Triangular(a = -1, m = 0, b = 1) -> y0 : Uniform(a = 0, b = 1)
| y1 = Triangular(a = -1, m = 0, b = 1) -> y1 : Uniform(a = 0, b = 1)
))
----------------------------------------------------------------------------------------------------
(| y0 = [x0]->[x0]
| y1 = [x1]->[x1]
| y2 = [x2]->[x2]
| y3 = [x3]->[x3]
)o(NatafIndependentCopulaEvaluation(IndependentCopula(4)->Normal(4)))
|
