A unified theory of stochastic ordering for Markov processes on partially ordered state spaces is developed. When such a space is not totally ordered, it can induce a range of stochastic orderings, none of which is equivalent to sample path comparisons. Such alternative orderings can be quite useful when analyzing multidimensional stochastic models such as queuing methods.
|Number of pages
|Proceedings of the IEEE Conference on Decision and Control
|Published - 1984
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization