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Introduction to Rare Event Simulation
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Catalogue Information
Nome campo
dettagli
Dewey Class
519.5
Titolo
Introduction to Rare Event Simulation ([EBook] /) / by James Antonio Bucklew.
Autore
Bucklew, James Antonio
Other name(s)
SpringerLink (Online service)
Pubblicazione
New York, NY : : Springer New York : : Imprint: Springer, , 2004.
Physical Details
XII, 268 p. : online resource.
Serie
Springer Series in Statistics
0172-7397
ISBN
9781475740783
Summary Note
This book presents a unified theory of rare event simulation and the variance reduction technique known as importance sampling from the point of view of the probabilistic theory of large deviations. This perspective allows us to view a vast assortment of simulation problems from a unified single perspective. It gives a great deal of insight into the fundamental nature of rare event simulation. Until now, this area has a reputation among simulation practitioners of requiring a great deal of technical and probabilistic expertise. This text keeps the mathematical preliminaries to a minimum with the only prerequisite being a single large deviation theory result that is given and proved in the text. Large deviation theory is a burgeoning area of probability theory and many of the results in it can be applied to simulation problems. Rather than try to be as complete as possible in the exposition of all possible aspects of the available theory, the book concentrates on demonstrating the methodology and the principal ideas in a fairly simple setting. The book contains over 50 figures and detailed simulation case studies covering a wide variety of application areas including statistics, telecommunications, and queueing systems. James A. Bucklew holds the rank of Professor with appointments in the Department of Electrical and Computer Engineering and in the Department of Mathematics at the University of Wisconsin-Madison. He is a Fellow of the Institute of Electrical and Electronics Engineers and the author of Large Deviation Techniques in Decision, Simulation, and Estimation.:
Contents note
1. Random Number Generation -- 2. Stochastic Models -- 3. Large Deviation Theory -- 4. Importance Sampling -- 5. The Large Deviation Theory of Importance Sampling Estimators -- 6. Variance Rate Theory of Conditional Importance Sampling Estimators -- 7. The Large Deviations of Bias Point Selection -- 8. Chernoff’s Bound and Asymptotic Expansions -- 9. Gaussian Systems -- 10. Universal Simulation Distributions -- 11. Rare Event Simulation for Level Crossing and Queueing Models -- 12. Blind Simulation -- 13. The (Over-Under) Biasing Problem in Importance Sampling -- 14. Tools and Techniques for Importance Sampling -- A. Convex Functions and Analysis -- B. A Covering Lemma -- C. Pseudo-Random Number Generator Programs -- References.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-1-4757-4078-3
Link alle Opere Legate
Riferimenti soggetto:
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Applied mathematics
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Appl.Mathematics/Computational Methods of Engineering
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Computer Communication Networks
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Computer communication systems
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Computer simulation
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Engineering mathematics
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Management science
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Operations research
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Operations Research, Management Science
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Probabilities
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Probability theory and stochastic processes
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Simulation and Modeling
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Statistics
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Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
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Authors:
Bucklew, James Antonio
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Corporate Authors:
SpringerLink (Online service)
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Series:
Springer Series in Statistics
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Classification:
519.5
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