Abstract
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.
Original language | English (US) |
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Pages (from-to) | 551-555 |
Number of pages | 5 |
Journal | Proceedings of the IEEE Conference on Decision and Control |
DOIs | |
State | Published - 1984 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization