Simulation / Sheldon M. Ross
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9780124158252
- QA273 .R67 2013
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North South University Library | Non-fiction | General Stacks | QA273.R67 2013 (Browse shelf(Opens below)) | 1 | Available | 36780 | ||
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North South University Library | Non-fiction | General Stacks | QA273.R67 2013 (Browse shelf(Opens below)) | 2 | Available | 36781 | ||
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North South University Library | Non-fiction | General Stacks | QA273.R67 2013 (Browse shelf(Opens below)) | 3 | Available | 43586 |
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QA273.P37 2002 Probability, random variables, and stochastic processes / | QA273.R67 2013 Simulation / | QA273.R67 2013 Simulation / | QA273.R67 2013 Simulation / | QA273.S56 1967 Probability : | QA273.S65 1987 Probability and stochastic processes / | QA273.T83 1962 An introduction to probabiliy and mathematical statistics / |
Includes bibliographical references and index.
"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".
Mathematics, Physics & Statistics
Computer Science & Engineering
Dilruba Rahman
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