Dynamic random Weyl sampling for drastic reduction of randomness in Monte Carlo integration

Hiroshi Sugita

Mathematics and Computers in Simulation (MATCOM), 2003, vol. 62, issue 3, 529-537

Abstract: 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.

Keywords: Numerical integration; Monte Carlo integration; i.i.d.-sampling; Pairwise independent sampling; Random Weyl sampling; Dynamic random Weyl sampling; Cryptographically secure pseudo-random generator (search for similar items in EconPapers)
Date: 2003
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:62:y:2003:i:3:p:529-537

DOI: 10.1016/S0378-4754(02)00231-8

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