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Titlebook: Essentials of Monte Carlo Simulation; Statistical Methods Nick T. Thomopoulos Book 2013 Springer Science+Business Media New York 2013 Mont

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書目名稱Essentials of Monte Carlo Simulation
副標(biāo)題Statistical Methods
編輯Nick T. Thomopoulos
視頻videohttp://file.papertrans.cn/316/315668/315668.mp4
概述Offers a "fundamentals" approach to developing Monte Carlo computer simulations.Illustrates the best ways to select input distributions and parameters with or without sample data.Author has published
圖書封面Titlebook: Essentials of Monte Carlo Simulation; Statistical Methods  Nick T. Thomopoulos Book 2013 Springer Science+Business Media New York 2013 Mont
描述.Essentials of Monte Carlo Simulation?.focuses?on?the fundamentals of Monte Carlo?methods using basic computer simulation techniques. The theories presented in this text deal with?systems that are too complex to solve analytically. As a result, readers are given?a?system of interest and constructs?using computer code, as well as?algorithmic models?to emulate how the system works internally. After the models are?run several?times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This?book features?11 comprehensive chapters, and discusses such key?topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate?useful real world?applications.??The text also contains an easy to read??presentation with minimal use of difficult mathematical concepts.??Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics.?.
出版日期Book 2013
關(guān)鍵詞Monte Carlo Simulations; Multivariate Random Variates; Random Number Generators; Simulation Models; Stat
版次1
doihttps://doi.org/10.1007/978-1-4614-6022-0
isbn_softcover978-1-4899-8608-5
isbn_ebook978-1-4614-6022-0
copyrightSpringer Science+Business Media New York 2013
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https://doi.org/10.1007/978-1-4614-6022-0Monte Carlo Simulations; Multivariate Random Variates; Random Number Generators; Simulation Models; Stat
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Book 2013sented in this text deal with?systems that are too complex to solve analytically. As a result, readers are given?a?system of interest and constructs?using computer code, as well as?algorithmic models?to emulate how the system works internally. After the models are?run several?times, in a random samp
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Choosing the Probability Distribution When No Data,
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Bettina Lamm Dipl.-Psych.iented towards el- trical machinery is not up to date and has not been changed in some co- tries almost since the end of the WWII. In spite of ma978-90-481-8051-6978-1-4020-9007-3Series ISSN 1612-1287 Series E-ISSN 1860-4676
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