| Regenerative Stochastic Simulation Contributor(s): Shedler, Gerald S. (Author) |
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ISBN: 0126393605 ISBN-13: 9780126393606 Publisher: Academic Press OUR PRICE: $72.22 Product Type: Hardcover - Other Formats Published: October 1992 Annotation: 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. * 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 * Focuses on simulations with an underlying stochastic process that can specified as a generalized semi-Markov process * Unique approach to simulation, with heavy emphasis on stochastic modeling * Includes engineering applications for computer, communication, manufacturing, and transportation systems |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - Stochastic Processes |
| Dewey: 620.001 |
| LCCN: 92023205 |
| Series: Statistical Modeling and Decision Science |
| Physical Information: 1.22" H x 6" W x 9.46" (1.75 lbs) 400 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |