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Focusing on statistical simulation, this book offers a programmer's perspective on essential tools and techniques. It details the R implementation of various simulation methods, enhancing comprehension through practical output examples. This approach facilitates better understanding and comparison of different statistical simulations.

Markov chain Monte Carlo methods were developed to provide the experimenter with realistic models. Written by two leading researchers, this up-to-date reference covers an important area of statistic which has many applications to engineering, aeronautics, biology, networks, and astronomy.