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arXiv · hep-ph/9601270

Discrepancy-based error estimates for Quasi-Monte Carlo. I: General formalism

Jiri Hoogland·Ronald Kleiss
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Abstract

We show how information on the uniformity properties of a point set employed in numerical multidimensional integration can be used to improve the error estimate over the usual Monte Carlo one. We introduce a new measure of (non-)uniformity for point sets, and derive explicit expressions for the various entities that enter in such an improved error estimate. The use of Feynman diagrams provides a transparent and straightforward way to compute this improved error estimate.

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Jiri Hoogland, Ronald Kleiss. 1996-01-23. Discrepancy-based error estimates for Quasi-Monte Carlo. I: General formalism. https://doi.org/10.1016/0010-4655(96)00084-7

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