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Statisticians Kroese, Thomas Taimre (both U. of Queensland), and Zdravko I. Botev (U. of Montreal) offer researchers and graduate and advanced graduate students a compendium of Monte Carlo methods, which are statistical methods that involve random experiments on a computer. There are a great many such methods being used for so many kinds of problems in so many fields that such an overall view is hard to find. Combining theory, algorithms, and applications, they consider such topics as uniform random number generation, probability distributions, discrete event simulation, variance reduction, estimating derivatives, and applications to network reliability. (Annotation (c)2011 Book News Inc. Portland, OR)

Statisticians Kroese, Thomas Taimre (both U. of Queensland), and Zdravko I. Botev (U. of Montreal) offer researchers and graduate and advanced graduate students a compendium of Monte Carlo methods, which are statistical methods that involve random experiments on a computer. There are a great many such methods being used for so many kinds of problems in so many fields that such an overall view is hard to find. Combining theory, algorithms, and applications, they consider such topics as uniform random number generation, probability distributions, discrete event simulation, variance reduction, estimating derivatives, and applications to network reliability. (Annotation (c)2011 Book News Inc. Portland, OR)

Statisticians Kroese, Thomas Taimre (both U. of Queensland), and Zdravko I. Botev (U. of Montreal) offer researchers and graduate and advanced graduate students a compendium of Monte Carlo methods, which are statistical methods that involve random experiments on a computer. There are a great many such methods being used for so many kinds of problems in so many fields that such an overall view is hard to find. Combining theory, algorithms, and applications, they consider such topics as uniform random number generation, probability distributions, discrete event simulation, variance reduction, estimating derivatives, and applications to network reliability. (Annotation (c)2011 Book News Inc. Portland, OR)

“Statisticians Kroese, Thomas Taimre (both U. of Queensland), and Zdravko I. Botev (U. of Montreal) offer researchers and graduate and advanced graduate students a compendium of Monte Carlo methods, which are statistical methods that involve random experiments on a computer. There are a great many such methods being used for so many kinds of problems in so many fields that such an overall view is hard to find. Combining theory, algorithms, and applications, they consider such topics as uniform random number generation, probability distributions, discrete event simulation, variance reduction, estimating derivatives, and applications to network reliability. (Annotation (c)2011 Book News Inc. Portland, OR)

Author Information

Dirk P. Kroese, PhD, is Australian Professorial Fellow in Statistics at The University of Queensland (Australia). Dr. Kroese has more than seventy publications in such areas as stochastic modeling, randomized algorithms, computational statistics, and reliability. He is a pioneer of the cross-entropy method and the coauthor of Simulation and the Monte Carlo Method, Second Edition (Wiley). Thomas Taimre, PhD, is a Postdoctoral Research Fellow at The University of Queensland. He currently focuses his research on Monte Carlo methods and simulation, from the theoretical foundations to performing computer implementations.  Zdravko I. Botev, PhD, is a Postdoctoral Research Fellow at the University of Montreal  (Canada). His research interests include the splitting method for rare-event simulation and kernel density estimation. He is the author of one of the most widely used free MATLAB® statistical software programs for nonparametric kernel density estimation.

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