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For times $t_1,\ldots,t_n$, the corresponding finite-dimensional distribution of a <stochastic process> $X$ is the <joint probability distribution> of the <random vector> $(X_{t_1},\ldots,X_{t_n})$. The collection of these distributions records every finite set of coordinates of the process.


Finite-dimensional distribution

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The joint probability distribution of <random variables> $X_1,\ldots,X_n$ is the <probability distribution> of the <random vector> $(X_1,\ldots,X_n)$. It records both the marginal distributions and their dependence.


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 Incoming links: Joint probability distribution