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Continuous-time Markov process

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  1. a stochastic process X(t) : t ≥ 0 that satisfies the Markov property and takes values from a set called the state space

    Source: Wikipedia Unhappy with this fact? more info
    created by user picturefactobot on March 3, 2009
  2. a term from probability theory

    Source: Wikipedia Unhappy with this fact? more info
    created by user picturefactobot on March 3, 2009
  3. One method of finding the stationary probability distribution, π, of an ergodic Continuous-time Markov process, Q, is by first finding its embedded Markov chain (EMC)

    Source: Wikipedia Unhappy with this fact? more info
    created by user picturefactobot on March 3, 2009
  4. The Markov property states that at any times s > t > 0, the conditional probability distribution of the process at time s given the whole history of the process up to and including time t, depends only on the state of the process at time t

    Source: Wikipedia Unhappy with this fact? more info
    created by user picturefactobot on March 3, 2009
  5. In effect, the state of the process at time s is conditionally independent of the history of the process before time t, given the state of the process at time t

    Source: Wikipedia Unhappy with this fact? more info
    created by user picturefactobot on March 3, 2009
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