Many readers will know the excellent "car rental / return" examples from the work of Prof. Howard. But I wonder if there are other good empirical / substantive examples of semi-markov (let's say finite) chains with discrete or continuous holding time distributions. Can readers provide interesting physical or substantive interpretations of the processes? What would it mean, for example, in your model, to say that a state has an equilibrium probability of 0.10, but a holding time weighted average share of 0.08? Could you provide an interpretative story about that state?
Perhaps I can stimulate some further comment with the idea that other threads show that nodal classification can be helpful in detecting network malfunction/intrusion. My current research is using related ideas to gauge imbalance in bike share systems. Are there other examples?
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