Approximating Integrals via Monte Carlo and Deterministic Methods

Approximating Integrals via Monte Carlo and Deterministic Methods
Author :
Publisher : OUP Oxford
Total Pages : 302
Release :
ISBN-10 : 9780191589874
ISBN-13 : 019158987X
Rating : 4/5 (87X Downloads)

Book Synopsis Approximating Integrals via Monte Carlo and Deterministic Methods by : Michael Evans

Download or read book Approximating Integrals via Monte Carlo and Deterministic Methods written by Michael Evans and published by OUP Oxford. This book was released on 2000-03-23 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to introduce graduate students and researchers to the primary methods useful for approximating integrals. The emphasis is on those methods that have been found to be of practical use, and although the focus is on approximating higher- dimensional integrals the lower-dimensional case is also covered. Included in the book are asymptotic techniques, multiple quadrature and quasi-random techniques as well as a complete development of Monte Carlo algorithms. For the Monte Carlo section importance sampling methods, variance reduction techniques and the primary Markov Chain Monte Carlo algorithms are covered. This book brings these various techniques together for the first time, and hence provides an accessible textbook and reference for researchers in a wide variety of disciplines.


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