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Regenerative Stochastic Simulation
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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. It develops probabilistic methods for simulation of discrete-event stochastic systems; emphasizes stochastic modeling and estimation procedures based on limit theorems for regenerative stochastic processes; includes engineering applications of discrete-even simulation to computer, communication, manufacturing, and transportation systems; and, focuses on simulations with an underlying stochastic process that can specified as a generalized semi-Markov process. The book also offers a unique approach to simulation, with heavy emphasis on stochastic modeling, and includes engineering applications for computer, communication, manufacturing, and transportation systems.
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