£119.20

Springer Strategies for Quasi-Monte Carlo - Operations Research

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Description

Strategies for Quasi-Monte Carlo provides a comprehensive framework for designing and analyzing randomized quasi-Monte Carlo (RQMC) methods. This volume, part of the International Series in Operations Research and Management Science, focuses on improving simulation efficiency through advanced mathematical strategies. The text explains how to structure problems to identify a small set of important variables, known as the effective dimension, while managing less significant variables. This approach allows for much higher efficiency in simulations. The book also covers the importance of smoothing techniques to enhance results. Readers will find practical illustrations involving Poisson processes and Gaussian processes. Because RQMC can beat traditional grids by a large margin, understanding these methods is vital for those working with low effective dimensions where RQMC provides an order-of-magnitude advantage in performance.

Key Features

Builds a professional framework to design and analyze randomized quasi-Monte Carlo (RQMC) strategies.

Explains how to identify effective dimension by isolating important variables from insignificant ones.

Includes detailed illustrations for practical application in Poisson processes and Gaussian processes.

Provides methods for smoothing to improve simulation outcomes and efficiency.

Demonstrates how RQMC outperforms traditional grids by a significant margin in many scenarios.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 August 1999
Listed Since
15 February 2007

Barcode

No barcode data available

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