Skorokhod's representation theorem

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In mathematics and statistics, Skorokhod's representation theorem is a result that shows that a weakly convergent sequence of probability measures whose limit measure is sufficiently well-behaved can be represented as the distribution/law of a sequence of random variables defined on a common probability space. It is named for the Ukrainian mathematician A.V. Skorokhod.

[edit] Statement of the theorem

Let μ_n, n ∈ N be a sequence of probability measures on a topological space S; suppose that μ_n converges weakly to some probability measure μ on S as n → ∞. Suppose also that the support of μ is separable. Then there exist random variables X_n, X defined on a common probability space (Ω, F, P) such that

• (X_n)_∗(P) = μ_n (i.e. μ_n is the distribution/law of X_n);
• X_∗(P) = μ (i.e. μ is the distribution/law of X); and
• X_n(ω) → X(ω) as n → ∞ for every ω ∈ Ω.

[edit] References

• Billingsley, Patrick (1999). Convergence of Probability Measures. New York: John Wiley & Sons, Inc.. ISBN 0-471-19745-9.  (see theorem 29.6)