Probability theory and stochastic processes Markov processes Concept
Markov chain
Summary
A Markov chain is a random process in which the next state depends only on the present state, and not on the earlier history. The node Markov chain gives the precise definition in discrete time with a countable state space.
Where this leads
6 pages build on this one.
Further reading
- Web https://en.wikipedia.org/wiki/Markov_chain, lead section
About this page
| Tag | 0G48PYM96Q |
|---|---|
| URI | m2://0G48PYM96Q |
| Aliases | discrete-time-markov-chain |
| Kind | concept |
| Writing | W1 stated |
| MSC | 60J10 |
| Specializes | Stochastic process |
| Same as |
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What this page needs for W2
- edge instance_of in: at least two examples (1 of 2)
- edge not_instance_of in: at least one non-example (0 of 1)
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What links here
Definitions
Special cases
Results about this
Used by
- Pólya's recurrence theorem
- Random walk on a group
- Hidden Markov model
- Green's function of a Markov process
- Particle filter