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Markov chain

A random process where the next state depends only on the current state, not on how it was reached.

A discrete random process \{X_i\} has the Markov (unit-memory) property if P(X_{n+1}\mid X_n,X_{n-1},\ldots,X_1) = P(X_{n+1}\mid X_n) for all n.

Examples

  • A two-state weather model where tomorrow depends only on today.

See also

stationary distribution transition matrix
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