Characterizing distributions of stochastic processes by linear operators

This report describes how the finite-dimensional marginal distributions of a stochastic process with values in an arbitrary measurable space can be calculated with linear operators. A 1-1 correspondence between certain algebraic structures and distributions of discrete processes is found. One obtains a novel access to stochastic processes, by showing a way to model their distributions purely by means from linear algebra.