Ross, Sheldon M. <br/><br/>
Simulation  [electronic resource] / 
Sheldon M. Ross. 
 - 5th ed. 
 - Amsterdam :  Academic Press,  2013. 
 - xii, 310 p. :  ill. 
<br/><br/>Includes bibliographical references and index. 
<br/><br/>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. 
<br/><br/> "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"-- 
<br/><br/><br/>Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. 
<br/><br/><label>ISBN: </label>9780124159716 (electronic bk.) 
<br/><br/><label>LCCN: </label>
<br/><br/><label>Subjects--Topical Terms: </label><br/>Random variables.<br/>Probabilities.<br/>Computer simulation.
<br/><br/><label>Index Terms--Genre/Form: </label><br/>Electronic books.
<br/><br/><label>LC Class. No.: </label>QA273  / .R82 2013 
<br/><br/><label>Dewey Class. No.: </label>519.2