Probability theory and stochastic processes Markov processes Concept
Stationary distribution
Summary
A stationary distribution of a Markov chain is a distribution of the state that does not change in one step of the chain. The node stationary distribution gives the precise definition.
Where this leads
9 pages build on this one.
Further reading
- Web https://en.wikipedia.org/wiki/Discrete-time_Markov_chain, Stationary distributions
About this page
| Tag | 0KRH5157WP |
|---|---|
| URI | m2://0KRH5157WP |
| Aliases | invariant-distribution, steady-state-distribution |
| Kind | concept |
| Writing | W0 stub |
| MSC | 60J10 |
| Specializes | Probability measure |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
Definitions
Used by
- Hamiltonian Monte Carlo
- Metropolis–Hastings algorithm
- Convergence to equilibrium of ergodic Markov chains
- Detailed balance
- Coupling from the past
- Recurrence and transience of states
- Markov chain mixing time
- Gibbs sampling
- Markov chain Monte Carlo