A Markov chain, named after Andrey Markov, is a mathematical system that undergoes transitions from one state to another, between a finite or countable number of possible states. It is a random process usually characterized as memoryless: the next state depends only on the current state and not on the sequence of events that preceded it. This specific kind of "memorylessness" is called the Markov property. Markov chains have many applications as statistical models of real-world processes.
Read more about Markov Chain: Introduction, Formal Definition, Markov Chains, Finite State Space, Reversible Markov Chain, Bernoulli Scheme, General State Space, Applications, Fitting, History
Famous quotes containing the word chain:
“By this unprincipled facility of changing the state as often, and as much, and in as many ways as there are floating fancies or fashions, the whole chain and continuity of the commonwealth would be broken. No one generation could link with the other. Men would become little better than the flies of a summer.”
—Edmund Burke (1729–1797)