NEW STOCHASTIC ORDERINGS FOR MARKOV PROCESSES ON PARTIALLY ORDERED SPACES.

Research output: Contribution to journalConference article

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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 languageEnglish (US)
Pages (from-to)551-555
Number of pages5
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
StatePublished - 1984
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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