TY  - BOOK
AU  - Ross,Sheldon M.
TI  - Simulation
SN  -  0124158250 (hardback)
U1  - 519.2 22
PY  - 2013///
CY  - San Diego
PB  - Academic Press / Elsevier
KW  - Random variables
KW  - BUEsh
KW  - Probabilities
KW  - Computer simulation
KW  - COMSCI
KW  - August2015
KW  - reading book
N1  - Index : p. 303-310; Includes bibliographical references; 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
N2  - "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"--
ER  -