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Rating: 
Summary: Not good for the beginner
Review: Even though this book contains a lot of things,but you can not konw exactly how to do them from the book.The whole book is something like introduction and result.If you are interested at random number algorithm, this book is OK.The best book of Monte Carlo Methods for the beginner is Basics, Volume 1, Monte Carlo Methods,though this book is quite expensive.
Rating: 
Summary: Random number algorithms
Review: Software developers will find this book very useful. It gives a thorough introduction to the types of RNGs available (linear congruential, lagged Fibonacci, etc.), as well as a thorough analysis of the strengths and weaknesses of each. The math is complete, but not intimidating. Algorithms are included for sampling from many different types of distributions (Beta, Weibull, etc.). A helpful discussion of generating independent streams of random numbers (i.e., on parallel processors or machines) is included. Also useful: a chapter on assessing the quality of RNGs, discussions of Gibbs and Latin Hypercube sampling, and bootstrapping. This book is "non-denominational". Many MC books focus on simulation in particular fields (such as physics). The focus here is on the science of random numbers itself. This short book has been extremely helpful in my implementation of Monte Carlo methods. The first 40 pages are virtually a daily reference for me. Any developer needing assistance and understanding of the types of random number generators available will find this small book extremely helpful.
Rating:
Summary: Random number algorithms
Review: Software developers will find this book very useful. It gives a thorough introduction to the types of RNGs available (linear congruential, lagged Fibonacci, etc.), as well as a thorough analysis of the strengths and weaknesses of each. The math is complete, but not intimidating. Algorithms are included for sampling from many different types of distributions (Beta, Weibull, etc.). A helpful discussion of generating independent streams of random numbers (i.e., on parallel processors or machines) is included. Also useful: a chapter on assessing the quality of RNGs, discussions of Gibbs and Latin Hypercube sampling, and bootstrapping. This book is "non-denominational". Many MC books focus on simulation in particular fields (such as physics). The focus here is on the science of random numbers itself. This short book has been extremely helpful in my implementation of Monte Carlo methods. The first 40 pages are virtually a daily reference for me. Any developer needing assistance and understanding of the types of random number generators available will find this small book extremely helpful.
Rating:
Summary: Great Reference Book !
Review: Very useful book if you plan to use Monte Carlo methods in your work. A timely topic + a highly respected authority in the field + good writing style = a great reference book !
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