Approximating Integrals Via Monte Carlo and Deterministic Methods

Erscheinungsjahr 2000
ISBN: 978-0-19-850278-4
Verlag: OUP Oxford

Buch, Englisch, 298 Seiten, Print PDF, Format (B × H): 161 mm x 240 mm, Gewicht: 617 g

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.

Autoren/Hrsg.

Evans, Michael

Swartz, Tim

Swartz, Timothy

Fachgebiete

• Mathematik | Informatik Mathematik Mathematische Analysis Reelle Analysis
• Mathematik | Informatik Mathematik Mathematische Analysis Integralrechnungen- und -gleichungen

Inhaltsverzeichnis

- 1: Introduction

- 2: Some basic tools

- 3: Algorithms for sampling from distributions

- 4: Approximating integrals via asymptotics

- 5: Multiple quadrature

- 6: Importance sampling

- 7: Markov Chain methods