Regenerative Stochastic Simulation

By

  • Gerald Shedler, IBM Research Divison

Simulation is a controlled statistical sampling technique that can be used to study complex stochastic systems when analytic and/or numerical techniques do not suffice. The focus of this book is on simulations of discrete-event stochastic systems; namely, simulations in which stochastic state transitions occur only at an increasing sequence of random times. The discussion emphasizes simulations on a finite or countably infinite state space.
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Audience

The presentation is self contained. Some knowledge of elementary probability theory, statistics, and stochastic models is necessary for an understanding of the theory and the examples. Many of the arguments use results often contained in a first year graduate course on stochastic process. A brief review of the necessary material is in Appendix A.

 

Book information

  • Published: October 1992
  • Imprint: ACADEMIC PRESS
  • ISBN: 978-0-12-639360-6


Table of Contents

Preface. Discrete-Event Simulations. Regenerative Stochastic Processes. Regenerative Simulation. Networks of Queues. Passage Times. Simulations With Simultaneous Events. Appendix A. Limit Theorems for Stochastic Processes. Appendix B. Random Number Generation.