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

نویسنده

  • Hiroshi Sugita
چکیده

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. © 2002 IMACS. Published by Elsevier Science B.V. All rights reserved.

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عنوان ژورنال:
  • Mathematics and Computers in Simulation

دوره 62  شماره 

صفحات  -

تاریخ انتشار 2003