Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. High Quality Content by WIKIPEDIA articles! In probability theory, a continuous-time Markov process is a stochastic process { X(t) : t >= 0 } that satisfies the Markov property and takes values from a set called the state space; it is the continuous-time version of a Markov chain. 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. 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.

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