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Copula.Rank.Region.RhoFootrule.UpperRightMoments

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    theorem ProbabilityTheory.Copula.RankRegion.RhoFootrule.RightData.integral_distance_cost (S : RightData) (f : ℝ → ℝ) (hf : Continuous f) :
    ∫ (x : Fin 2 → ↑unitInterval), f |↑(x 0) - ↑(x 1)| ∂S.copula.toMeasure = 2 * ∑ i : S.Index, S.weight i * ∫ (s : ↑unitInterval), f (S.distance i ↑s)
    theorem ProbabilityTheory.Copula.RankRegion.RhoFootrule.RightData.integral_distance_reversed (S : RightData) (f : ℝ → ℝ) :
    ∫ (s : ↑unitInterval), f (S.w + (↑S.N + 1) * S.v - S.v * ↑s) = ∫ (s : ↑unitInterval), f (S.w + ↑S.N * S.v + S.v * ↑s)
    theorem ProbabilityTheory.Copula.RankRegion.RhoFootrule.RightData.integral_distance_formula (S : RightData) (f : ℝ → ℝ) (hf : Continuous f) :
    ∫ (x : Fin 2 → ↑unitInterval), f |↑(x 0) - ↑(x 1)| ∂S.copula.toMeasure = 2 * (↑S.N + 1) * S.w * f (S.w + ↑S.N * S.v) + 2 * ↑S.N * (↑S.N + 1) * S.v * ∫ (s : ↑unitInterval), f (S.w + ↑S.N * S.v + S.v * ↑s)
    theorem ProbabilityTheory.Copula.RankRegion.RhoFootrule.RightData.integral_sq_distance (S : RightData) :
    ∫ (x : Fin 2 → ↑unitInterval), (↑(x 0) - ↑(x 1)) ^ 2 ∂S.copula.toMeasure = (S.w + ↑S.N * S.v) ^ 2 + 2 * ↑S.N * (↑S.N + 1) * (S.w + ↑S.N * S.v) * S.v ^ 2 + 2 / 3 * ↑S.N * (↑S.N + 1) * S.v ^ 3
    theorem ProbabilityTheory.Copula.RankRegion.RhoFootrule.RightData.rho (S : RightData) :
    S.copula.spearmanRho = 1 - 6 * ((S.w + ↑S.N * S.v) ^ 2 + 2 * ↑S.N * (↑S.N + 1) * (S.w + ↑S.N * S.v) * S.v ^ 2 + 2 / 3 * ↑S.N * (↑S.N + 1) * S.v ^ 3)