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2. for all measurable sets <math>F_{i} \subseteq \mathbb{R}^{n}</math>,<math>m \in \mathbb{N}</math>
:<math>\nu_{t_{1} \dots t_{k}} \left( F_{1} \times \dots \times F_{k} \right) = \nu_{t_{1} \dots t_{k}, t_{k + 1}, \dots , t_{k+m}} \left( F_{1} \times \dots \times F_{k} \times \underbrace{\mathbb{R}^{n} \times \dots \times \mathbb{R}^{n}}_{m} \right).</math>
Then there exists a [[probability space]] <math>(\Omega, \mathcal{F}, \mathbb{P})</math> and a stochastic process <math>X : T \times \Omega \to \mathbb{R}^{n}</math> such that
:<math>\nu_{t_{1} \dots t_{k}} \left( F_{1} \times \dots \times F_{k} \right) = \mathbb{P} \left( X_{t_{1}} \in F_{1}, \dots, X_{t_{k}} \in F_{k} \right)</math>
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