Regularity of Stochastic Processes: A Theory Based on Directional Convexity

Author:

Meester Ludolf E.,Shanthikumar J. George

Abstract

We define a notion of regularity ordering among stochastic processes called directionally convex (dcx) ordering and give examples of doubly stochastic Poisson and Markov renewal processes where such ordering is prevalent. Further-more, we show that the class of segmented processes introduced by Chang, Chao, and Pinedo [3] provides a rich set of stochastic processes where the dcx ordering can be commonly encountered. When the input processes to a large class of queueing systems (single stage as well as networks) are dcx ordered, so are the processes associated with these queueing systems. For example, if the input processes to two tandem /M/c1→/M/c2→…→/M/cm queueing systems are dcx ordered, so are the numbers of customers in the systems. The concept of directionally convex functions (Shaked and Shanthikumar [15]) and the notion of multivariate stochastic convexity (Chang, Chao, Pinedo, and Shanthikumar [4]) are employed in our analysis.

Publisher

Cambridge University Press (CUP)

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Statistics, Probability and Uncertainty,Statistics and Probability

Reference18 articles.

1. 5. Meester L.E. (1990). Contributions to the theory and applications of stochastic convexity. Ph.D. thesis, Department of Statistics, University of California, Berkeley.

2. Stability and bounds for single server queues in random environment

3. Monotonicity results for queues with doubly stochastic Poisson arrivals: Ross's conjecture

4. Stochastic convexity for multidimensional processes and its applications

5. 6. Meester L.E. & Shanthikumar J.G. (1990). Stochastic convexity on general space. Technical Report, University of California, Berkeley.

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