# Kolmogorov equation

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An equation of the form

 (1)

(the inverse, backward or first, equation; ), or of the form

 (2)

(the direct, forward or second, equation; ), for the transition function , , , , being a measurable space, or its density , if it exists. For the transition function the condition

is adjoined to equation (1), and the condition

is adjoined to equation (2), where is the indicator function of the set ; in this case the operator is an operator acting in a function space, while acts in a space of generalized measures.

For a Markov process with a countable set of states, the transition function is completely determined by the transition probabilities (from the state at instant to the state at instant ), for which the backward and forward Kolmogorov equations have (under certain extra assumptions) the form

 (3)
 (4)

where

 (5)

In the case of a finite number of states, equations (3) and (4) hold, provided that the limits in (5) exist.

Another important class of processes for which the question of the validity of equations (1) and (2) has been studied in detail is the class of processes of diffusion type. These are defined by the condition that their transition functions , , , satisfy the following conditions:

a) for each and ,

uniformly in , ;

b) there exist functions and such that for every and ,

uniformly in , . If the density exists, then (under certain extra assumptions) the forward equation

holds (for and ) (also called the Fokker–Planck equation), while the backward equation (for and ) has the form

#### References

 [1] A.N. Kolmogorov, "Ueber die analytischen Methoden in der Wahrscheinlichkeitsrechnung" Math. Ann. , 104 (1931) pp. 415–458 [2] I.I. [I.I. Gikhman] Gihman, A.V. [A.V. Skorokhod] Skorohod, "The theory of stochastic processes" , 2 , Springer (1979) (Translated from Russian)