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Author Ross, Sheldon M.
Title Simulation / Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California.
Published Amsterdam : Academic Press, 2013.
Book Cover
LOCATION CALL # STATUS
 Floor4  QA273 .R82 2013    DUE 02-28-15
  
Edition Fifth edition.
Description xii, 310 pages : illustrations ; 24 cm
Content Type text
Format volume
Bibliography Includes bibliographical references and index.
Contents 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.
Summary "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"-- Provided by publisher.
Subject Random variables.
Probabilities.
Computer simulation.
ISBN 9780124158252 (hardback)
0124158250 (hardback)
OCLC number 741548323