The transition probability Pij is the conditional probability that a Markov chain moves to state j on its next step given that its current state is i.
At state x, the holding probability of a discrete-time Markov chain is the self-transition probability P(x,x). It is the conditional probability that the next state remains x. In a nearest-neighbour birth-death chain, it is 1−px−qx, where px and qx are the probabilities of stepping right and left. Holding changes the elapsed time but not the embedded chain of actual moves or its boundary exit probabilities.
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- Stochastic matrix
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- Markov process
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- Absorbing state
- Accessible state of a Markov chain
- Barker acceptance probability
- Bellman equation
- Channel capacity
- Continuous-time Markov chain convergence theorem
- Expected finite-horizon occupation time
- Finite-seed local extinction in the voter model
- Five-state barrier example for simulated annealing
- Five-state harmonic absorption example
- Fixed-temperature law of simulated annealing
- Flips versus erasures in a binary channel
- Frozen-age approximation in a multi-state model
- Irreducible Markov chain
- Irreversible three-state disease model
- Markov chain
- Markov decision process
- Mixed panel and exact-death likelihood
- Occupation time of a continuous-time Markov chain
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- Progressive illness-death model
- Random adjacent transposition shuffle
- Simple random walk on the integer line
- Simulated annealing
- Square-pulse resonance profile
- Stochastic matrix
- Transition density
- Unitary time evolution
- Weakly symmetric channel capacity
- Weak-pulse Ramsey spectrum
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