Dynamic random Weyl sampling for drastic reduction of randomness in Monte Carlo integration
To reduce randomness drastically in Monte Carlo (MC) integration, we propose a pairwise independent sampling, the dynamic random Weyl sampling (DRWS). DRWS is applicable even if the length of random bits to generate a sample may vary. The algorithm of DRWS is so simple that it works very fast, even though the pseudo-random generator, the source of randomness, might be slow. In particular, we can use a cryptographically secure pseudo-random generator for DRWS to obtain the most reliable numerical integration method for complicated functions.
Year of publication: |
2003
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Authors: | Sugita, Hiroshi |
Published in: |
Mathematics and Computers in Simulation (MATCOM). - Elsevier, ISSN 0378-4754. - Vol. 62.2003, 3, p. 529-537
|
Publisher: |
Elsevier |
Subject: | Numerical integration | Monte Carlo integration | i.i.d.-sampling | Pairwise independent sampling | Random Weyl sampling | Dynamic random Weyl sampling | Cryptographically secure pseudo-random generator |
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