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Random and Quasi-Random Point Sets (Paperback, Softcover reprint of the original 1st ed. 1998) Loot Price: R2,996
Discovery Miles 29 960
Random and Quasi-Random Point Sets (Paperback, Softcover reprint of the original 1st ed. 1998): J. Beck

Random and Quasi-Random Point Sets (Paperback, Softcover reprint of the original 1st ed. 1998)

J. Beck; Edited by Peter Hellekalek, Gerhard Larcher; Contributions by P. Hellekalek, P. Hickernell, G.L. Archer, P. L'Ecuyer, H. Niederreiter, S. Tezuka, C. Xing

Series: Lecture Notes in Statistics, 138

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This volume is a collection of survey papers on recent developments in the fields of quasi-Monte Carlo methods and uniform random number generation. We will cover a broad spectrum of questions, from advanced metric number theory to pricing financial derivatives. The Monte Carlo method is one of the most important tools of system modeling. Deterministic algorithms, so-called uniform random number gen erators, are used to produce the input for the model systems on computers. Such generators are assessed by theoretical ("a priori") and by empirical tests. In the a priori analysis, we study figures of merit that measure the uniformity of certain high-dimensional "random" point sets. The degree of uniformity is strongly related to the degree of correlations within the random numbers. The quasi-Monte Carlo approach aims at improving the rate of conver gence in the Monte Carlo method by number-theoretic techniques. It yields deterministic bounds for the approximation error. The main mathematical tool here are so-called low-discrepancy sequences. These "quasi-random" points are produced by deterministic algorithms and should be as "super" uniformly distributed as possible. Hence, both in uniform random number generation and in quasi-Monte Carlo methods, we study the uniformity of deterministically generated point sets in high dimensions. By a (common) abuse oflanguage, one speaks of random and quasi-random point sets. The central questions treated in this book are (i) how to generate, (ii) how to analyze, and (iii) how to apply such high-dimensional point sets."

General

Imprint: Springer-Verlag New York
Country of origin: United States
Series: Lecture Notes in Statistics, 138
Release date: 2001
First published: 1998
Contributors: J. Beck
Editors: Peter Hellekalek • Gerhard Larcher
Contributors: P. Hellekalek • P. Hickernell • G.L. Archer • P. L'Ecuyer • H. Niederreiter • S. Tezuka • C. Xing
Dimensions: 235 x 155 x 18mm (L x W x T)
Format: Paperback
Pages: 334
Edition: Softcover reprint of the original 1st ed. 1998
ISBN-13: 978-0-387-98554-1
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
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LSN: 0-387-98554-9
Barcode: 9780387985541

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