Approximating Integrals via Monte Carlo and Deterministic Methods

Integrals are one of the primary computational tools in mathematics, and hence are of great importance in just about any numerate discipline, including statistics, mathematical finance, computer science and engineering. Although it is occasionally possible to compute integrals exactly this is typically not the case. In these situations it becomes necessary to approximate integrals. This book covers all the most useful approximation techniques so far discovered; the first time that all such techniques have been included in a single book and at a level accessible for students. In particular, it includes a complete development of the material needed to construct the highly popular Markov Chain Monte Carlo (MCMC) methods.