Simulation / Sheldon M. Ross.
Material type:
TextPublication details: Amsterdam : Elsevier Inc, 2013.Edition: Fifth editionDescription: xii, 310 pages : illustrations ; 24 cmISBN: - 9780124158252
- 519.2 23
- QA273 .R82 2013
| Item type | Current library | Collection | Call number | Vol info | Status | Date due | Barcode | |
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Main Long
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Martin Oduor-Otieno Library This item is located on the library Second Floor | Non-fiction | QA273 .R82 2013 (Browse shelf(Opens below)) | 29928/19 | Available | MOOL19070113 |
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| QA273 .H694 1997 Probability and statistical inference / | QA273 .H694 1997 Probability and statistical inference / | QA273 .M225 2004 Multivariate probability / | QA273 .R82 2013 Simulation / | QA273 .R864 2014 An introduction to measure-theoretic probability / | QA273 .R8647 2014 Introduction to probability / | QA273 .T48 2012 Understanding probability / |
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"--
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