Details, Explanation and Meaning About Chapman-Kolmogorov equation

Chapman-Kolmogorov equation Guide, Meaning , Facts, Information and Description

In mathematics, specifically in probability theory, and yet more specifically in the theory of stochastic processes, the Chapman-Kolmogorov equation is an identity relating the joint probability distributions of different sets of coordinates on a stochastic process.

Suppose that {fi} is an indexed collection of random variables, that is, a stochastic process. Let

be the joint probability density function of the values of the random variables f1 to fn. Then, the Chapman-Kolmogorov equation is

Particularization to Markov chains

When the stochastic process under consideration is Markovian, the Chapman-Kolmogorov equation is equivalent to an identity on transition densities.

When the probability distribution on the state space of a Markov chain is discrete, the Chapman-Kolmogorov equations can be expressed in terms of (possibly infinite-dimensional) matrix multiplication, thus:

where P(t) is the transition matrix, i.e., if Xt is the state of the process at time t, then for any two points i and j in the state space, we have

See also

examples of Markov chains


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