Quasi-Monte Carlo method for in finitely divisible random vectors via series representations

Junichi Imai, Reiichiro Kawai

研究成果: Article査読

10 被引用数 (Scopus)


An infinitely divisible random vector without Gaussian component admits representations of shot noise series. Due to possible slow convergence of the series, they have not been investigated as a device for Monte Carlo simulation. In this paper, we investigate the structure of shot noise series representations from a simulation point of view and discuss the effectiveness of quasi-Monte Carlo methods applied to series representations. The structure of series representations in nature tends to decrease their effective dimension and thus increase the efficiency of quasi-Monte Carlo methods, thanks to the greater uniformity of low-discrepancy sequence in the lower dimension. We illustrate the effectiveness of our approach through numerical results of moment and tail probability estimations for stable and gamma random variables.

ジャーナルSIAM Journal on Scientific Computing
出版ステータスPublished - 2010

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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