Simulation
"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-st…
Read More ↓Title Statements
- Full title :Simulation / Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California.
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"--
Read More ↓Edition Statements
- Publication Date:2013.
- Edition:Fifth edition
Publication Statements
- Publisher(s):Academic Press
- Place of Publication:Amsterdam
- Language:eng
- Publication Date:2013.
The Physical Object
- Description:xii, 310 pages : : illustrations ; : 24 cm
Edition Identifiers
- ISBN:9780124158252, 0124158250
- oclc:ocn741548323
- LC Classification:QA273
- Dewey Decimal:519.2
Table of Contents
Elements of probability -- Random numbers -- Generating discrete random variables -- Generating continuous random variables -- The multivariate normal distribution and copulas -- The discrete event simulation approach -- Statistical analysis of simulated data -- Variance reduction techniques -- Additional variance reduction techniques -- Statistical validation techniques -- Markov chain Monte Carlo methods.
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