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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. As part of the International Series in Operations Research & Management Science, this volume focuses on increasing simulation efficiency by addressing effective dimension and smoothing. The text explores how to structure problems to reveal a small set of important variables, which helps manage the effective dimension of a simulation. It includes many illustrations regarding Poisson processes and Gaussian processes to demonstrate these techniques in practice. By utilizing low effective dimension, RQMC offers an order-of-magnitude improvement over traditional methods, beating grids by a large margin. This book is an essential resource for those working in operations research and management science who require advanced simulation strategies.

Key Features

This Springer publication builds a detailed framework to design and analyze randomized quasi-Monte Carlo (RQMC) strategies.

The text explains how to structure problems to identify a small set of important variables to manage effective dimension.

It provides numerous illustrations for practical application in problems involving Gaussian processes or Poisson processes.

The book demonstrates how RQMC outperforms grids by a large margin through improved simulation efficiency.

This volume is part of the International Series in Operations Research & Management Science, number 22.

Product Specifications

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

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