02523cam a2200361 i 450000100090000000300090000900500170001800800410003502000270007602000290010304000330013208200190016510000370018424501280022125000190034926400550036830000450042333600260046833700280049433800270052250400520054950504130060152008040101465000360181865000320185465000320188665100100191865300230192865500170195194200120196899900170198095201640199717451335EG-ScBUE20241109110913.0120904s2013    caua   f b    001 0 eng d  a 0124158250 (hardback)  a9780124158252 (hardback)  aDLCbengerdacDLCdEG-ScBUE04a519.2222bROS1 aRoss, Sheldon M.,eauthor.9734810aSimulation /cSheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California.  aFifth edition. 1aSan Diego, CA :bAcademic Press / Elsevier,c2013.  axii, 310 pages :billustrations ;c24 cm  2rdacontentatextbtxt  2rdamediaaunmediatedbn  2rdacarrieravolumebnc  aIncludes bibliographical references and index.
8 aMachine 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.  a"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"-- 7aRandom variables.2BUEsh918426 7aProbabilities.2BUEsh93494 7aComputer simulation.2BUEsh  2BUEsh  bCOMSCIcAugust2015  vReading book  2ddccBB  c20521d20493  00102ddc40708BaccahaMAINbMAINc1STd2015-08-16epurchaseg425.00h21759l1o519.2 ROSp000030751r2025-07-15 00:00:00s2015-11-10v531.00w2015-08-16yBB