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This abstract example of an absorbing Markov chain provides three basic measurements: The fundamental matrix ... is the mean number of times the process is in state ... given that it started in state ... ... . The absorption probability matrix shows the probability of each transient state being absorbed by the two absorption states, 1 and 7. The mean time for each transient state to be absorbed is shown in the absorption time matrix. The graph shows all the transient states, 2, 3, 4, 5, 6, and 8, and the two absorbing states, 1 and 7, together with all the probabilities allowed between the states. You can vary the probability of the transition from 2 to 1 with the slider. Because the sum of the probabilities is 1, for each state's total transitions, the transition probability for the transition from 2 to 3 is internally computed to sum to 1 when you drag the slider.

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      EUN,LOM,LRE4,work-cmr-id:262648,http://demonstrations.wolfram.com:http://demonstrations.wolfram.com/AbsorbingMarkovChain/,ilox,learning resource exchange,LRE metadata application profile,LRE

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