In probability theory, a Markov kernel (also known as a stochastic kernel or probability kernel) is a map that in the general theory of Markov processes plays the role that the transition matrix does in the theory of Markov processes with a finite state space. == Formal definition == Let ( X , A ) {\displaystyle (X,{\mathcal {A}})} and ( Y , B ) {\displaystyle (Y,{\mathcal {B}})} be measurable spaces.
In probability theory, a Markov kernel (also known as a stochastic kernel or probability kernel) is a map that in the general theory of Markov processes plays the role that the transition matrix does in the theory of Markov processes with a finite state space. == Formal definition == Let ( X , A ) {\displaystyle (X,{\mathcal {A}})} and ( Y , B ) {\displaystyle (Y,{\mathcal {B}})} be measurable spaces.
Source: Wikipedia "Markov kernel" · CC BY-SA 4.0
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