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Stochastic Simulation: Algorithms and Analysis (Stochastic Modelling and Applied Probability) (Englisch) Taschenbuch – 28. Dezember 2009

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From the reviews:

"The adequate statistical simulation of random quantities is one of the challenges of this century. Therefore, sampling-based computational methods have become a fundamental part of the numerical toolset of both practitioners and researchers … . This book provides a descriptive treatment of a variety of such sampling-based methods. Some steps to the mathematical analysis of their convergence properties and diverse applications are sketched as well. … this book is of potential interest to many researchers, students and instructors." (Henri Schurz, Zentralblatt MATH, Vol. 1126 (3), 2008)

"This is a very interesting book for all who are interested in stochastic simulations. … the book is designed as a potential teaching and learning tool for use in a wide variety of courses. … it is a book that should be on the bookshelf of everybody who is seriously interested in stochastic simulations." (EMS Newsletter, September, 2008)

"The present book provides a broad treatment of sampling-based computational methods, as well as accompanying mathematical analysis of the convergence properties of these methods for a wide range of stochastic application problems. … A set of exercises … is also given at the end of each chapter. This book will be a reference of great value for researchers in probability, statistics, operations research, economics, finance, and engineering … . It would also be perfect as a textbook for graduate seminars or courses in stochastic simulation." (Mou-Hsiung Chang, Siam Review, Vol. 51 (1), 2009)

"This book is intended to provide a broad treatment of the basic ideas and algorithms associated with sampling-based methods, often referred to as Monte Carlo algorithms or stochastic simulation. … the book will be very useful to students and researchers from a wide range of disciplines." (John P. Lehoczky, Mathematical Reviews, Issue 2009 c)

"Stochastic Simulation, written by two prominent researchers in applied probability, is an outgrowth of that maturation. The authors’ goal is not to tell the reader everything known about simulation, nor is it to give a collection of recipes, but rather to provide insight into analyzing problems via simulation. … The book would make an excellent text for a graduate course in simulation, especially in a mathematical sciences department." (Peter C. Kiessler, Journal of the American Statistical Association, Vol. 104 (486), June, 2009)


Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value. -- Dieser Text bezieht sich auf eine andere Ausgabe: Gebundene Ausgabe.

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Amazon.com: 3 Rezensionen
3 von 5 Kunden fanden die folgende Rezension hilfreich
Good Book 6. Januar 2011
Von A purchaser of the book - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
I've never bothered to review any book on Amazon prior to this note, but I felt the book was unduly trashed in the "grad student" review and I wanted to even the score a bit. I purchased the book and have used it along side Glasserman's (very useful) book for financial applications. I found the book to be a nice companion to the Glasserman book, generally going into greater mathematical detail.
0 von 2 Kunden fanden die folgende Rezension hilfreich
Five Stars 22. Juli 2014
Von Amazon Customer - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
purchased them for my son when he was doing his ph,d
5 von 16 Kunden fanden die folgende Rezension hilfreich
Awful book 8. April 2010
Von grad student - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
The introduction states the book will be useful for "readers with backgrounds ranging from an exposure to introductory probability to a much more advanced knowledge of the area." Try reading the first two pages with an "exposure" to "introductory" probability. Not likely. The book then goes on to list 2 full pages of notation explanations. This is completely separate from the ad-hoc notation explanations that appear in the text. It goes without saying that the notation the authors chose is confusing, tedious and distracting. The book is basically a horribly-explained tutorial on simulation experiment design. Most of all, it's undeniably dense, and the material is made much more complicated than necessary.
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