In the theory of Markovian stochastic processes within probability theory, the Chapman-Kolmogorov equation is an identity relating the joint probability distributions of different sets of coordinates on a stochastic process. It was derived independently by the British mathematician Sydney Chapman and the Russian mathematician Andrey Kolmogorov, and it is used prominently in modern variational Bayesian methods.
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Chapman-Kolmogorov equation
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In mathematics, specifically in the theory of Markovian stochastic processes in probability theory, the Chapman-Kolmogorov equation (CKE) is an identity relating the joint probability distributions of different sets of coordinates on a stochastic process.
Attributed To: Andrey Kolmogorov, Lead sentence
The equation was derived independently by both the British mathematician Sydney Chapman and the Russian mathematician Andrey Kolmogorov.
Principal Result Of: Andrey Kolmogorov, Lead sentence of the article on the result
The equation was derived independently by both the British mathematician Sydney Chapman and the Russian mathematician Andrey Kolmogorov.
View the SourceChapman-Kolmogorov equation (Wikipedia)
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