The Annals of Probability · 1993 · 22 citations · 0 references
Natural SciencesMathematicsMarkov Decision ProcessesProbability TheoryStochastic ProcessesMarkov ProcessesMeasure-theoretic ProbabilityProbability DistributionsProbability InequalitiesProbability SpacesStochastic CalculusProduct Probability Spaces
Section 6 is self‑contained and can be read independently of earlier sections. The paper develops an integral representation of dominated linear functionals and investigates the existence of probability distributions with specified marginals under weaker assumptions. The authors prove Theorem 1 to provide the integral representation and then apply Theorem 7 to analyze existence of distributions with given marginals. The results include a deduction of the Blackwell–Stein–Sherman–Cartier theorem, capacity results, necessary and sufficient conditions for sequences of measures to arise from martingales, upper semi‑martingales, or sums of independent variables, and an alternative definition of the Lévy–Prokhorov distance.
First an integral representation of a continuous linear functional dominated by a support function in integral form is given (Theorem 1). From this the theorem of Blackwell-Stein-Sherman-Cartier [2], [20], [4], is deduced as well as a result on capacities alternating of order 2 in the sense of Choquet [5], which includes Satz 4.3 of [23] and a result of Kellerer [10], [12], under somewhat stronger assumptions. Next (Theorem 7), the existence of probability distributions with given marginals is studied under typically weaker assumptions, than those which are required by the use of Theorem 1. As applications we derive necessary and sufficient conditions for a sequence of probability measures to be the sequence of distributions of a martingale (Theorem 8), an upper semi-martingale (Theorem 9) or of partial sums of independent random variables (Theorem 10). Moreover an alternative definition of Levy-Prokhorov's distance between probability measures in a complete separable metric space is obtained (corollary of Theorem 11). Section 6 can be read independently of the former sections.