Essentials of Monte Carlo Simulation: Statistical Methods for Building Simulation Models - Data Analysis & Risk Assessment for Finance, Engineering & Scientific Research
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Essentials of Monte Carlo Simulation: Statistical Methods for Building Simulation Models - Data Analysis & Risk Assessment for Finance, Engineering & Scientific Research
$72.07
$131.04
45% Off
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Description
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.
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Reviews
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Verified Buyer
5
This book fills a missing gap in the spectrum of Monte Carlo texts. At one extreme you have the works of Kelton and Law (and the like) which, while excellent, are encyclopedic in their approach and targeted to advanced students. At the other you have softer, more pedestrian introductions aimed at individuals with little or no background in the field. This book falls in between.I should note that I took a PhD level course in Monte Carlo methods from the author while he was on the faculty of the Illinois Institute of Technology. While our official text was Kelton and Law, this book reads like my course notes - a succinct and utterly relevant distillation of the main points of Kelton and Law. Of course, there is also plenty of unique material that make the book worthwhile in its own right.Finally, this book is extremely practical - it's for those who actually want to do Monte Carlo. It's not program or language specific (it won't tell you anything about how to use @RISK) but gives you all the necessary algorithms in the form of pseudo-code to utilize them in any programming language. It is an absolutely invaluable tool to have on hand when you are struggling with modeling problems.
