A Markov diffusion is a continuous-path <Markov process> whose local evolution is described by a drift vector and diffusion matrix. For sufficiently regular coefficients, its <infinitesimal generator> is a second-order differential operator and its conditional expectations satisfy a <Kolmogorov backward equation>.


Markov diffusion

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A Markov process is a <stochastic process> for which, conditional on the present state, the future is independent of the past. Its transition probabilities therefore determine every finite-dimensional distribution once the initial distribution is known.


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