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Cyclic Chains:
In Markov Chains the current state of the system depends on all previous states. It is a stochastic process. Sometimes transition probability matrices are different from State I to State II, State II to State III etc and from cyclic chains which repeat in the same order.Recurrent State:
A state is recurrent if it is certain to take place again, given that it has happened at least once, otherwise it is said to be transient. In other words, a transient state will take place only a limited number of times and then go away forever whereas the recurrent state is permanent. If a process is finite (i.e. has a finite number of states) and is irreducible, then all states are recurrent. This is the most common form of Markov Chain in applications.
what areas can linear programming be applied in managerial accounting?
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