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" Simulation / "
Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California
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BL
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| Record Number
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622408
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dltt
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| Main Entry
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Ross, Sheldon M
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| Title & Author
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Simulation /\ Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California
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| Edition Statement
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Fifth edition
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| Page. NO
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xii, 310 pages :: illustrations ;; 24 cm
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| ISBN
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9780124158252 (hardback)
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: 0124158250 (hardback)
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Includes bibliographical references and index
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| Contents
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Machine generated contents note: Preface; Introduction; Elements of Probability; Random Numbers; Generating Discrete Random Variables; Generating Continuous Random Variables; The Discrete Event Simulation Approach; Statistical Analysis of Simulated Data; Variance Reduction Techniques; Statistical Validation Techniques; Markov Chain Monte Carlo Methods; Some Additional Topics; Exercises; References; Index
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| Abstract
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"In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"--
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| Subject
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Random variables
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Probabilities
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Computer simulation
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| Dewey Classification
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519.2
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| LC Classification
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QA273.R82 2013
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