Continuous-Time Markov Models
In the previous chapter we studied stochastic models of randomly evolving systems that are observed at discrete-times n = 0, 1, 2,..., etc., with X n being the state of the system at time n. In this chapter we shall consider randomly evolving systems that are observed continuously at all times t ≥ 0, with X(t) being the state of the system at time t. The set of states that the system can be in at any given time is called the state space of the system and is denoted by S.
KeywordsSojourn Time Rate Matrix Computational Problem Transition Probability Matrix Repair Time
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