Title: Using Box-Muller with low discrepancy points
Authors: Pillards, Tim ×
Cools, Ronald #
Issue Date: 2006
Publisher: Springer-Verlag Berlin Heidelberg
Host Document: Lecture Notes in Computer Science vol:3984 pages:780-788
Conference: Computational Science and Its Applications - ICCS 2006 location:Glasgow, United Kingdom date:May 8-11, 2006
Abstract: To use quasi-Monte Carlo methods, the integral is usually first (implicitly) transformed to the unit cube. Integrals weighted with the multivariate normal density are usually transformed to the unit cube with the inverse of the multivariate normal cumulative distribution function. However, other transformations are possible, amongst which the transformation by Box and Muller. The danger in using a non-separable transformation is that it might break the low discrepancy structure which makes quasi-Monte Carlo converge faster than regular Monte Carlo. We examine several transformations visually, theoretically and practically and show that it is sometimes preferable to use other transformations than the inverse cumulative distribution function.
ISBN: 978-3-540-34079-9
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Numerical Analysis and Applied Mathematics Section
× corresponding author
# (joint) last author

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