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. The first half of the book focuses on general methods, whereas the second half discusses model-specific algorithms.pGiven 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.pSA, ren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of Engineering at Stanford University.From the reviews:pThe 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 a ] . 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. a ] this book is of potential interest to many researchers, students and instructors. (Henri Schurz, Zentralblatt MATH, Vol. 1126 (3), 2008)