Comparison of random number generators via Fourier transform

Research output: Contribution to journalArticle

Abstract

In this paper, we investigate simple yet practical schemes to generate random variates from the characteristic function of any continuous distribution. We discuss the generation of non-uniform random variates from a uniform random number generator. The inverse of the cumulative distribution function is derived from its characteristic function via the fast Fourier transform. We conduct several numerical experiments to assess the accuracy and efficiency of the schemes.

Original languageEnglish
Pages (from-to)237-259
Number of pages23
JournalMonte Carlo Methods and Applications
Volume19
Issue number3
DOIs
Publication statusPublished - 2013 Oct 1

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Random number Generator
Characteristic Function
Fourier transform
Fourier transforms
Cumulative distribution function
Continuous Distributions
Fast Fourier transform
Fast Fourier transforms
Distribution functions
Numerical Experiment
Experiments

Keywords

  • Fourier transform
  • infinitely divisible distribution
  • Monte Carlo method

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics

Cite this

Comparison of random number generators via Fourier transform. / Imai, Junichi.

In: Monte Carlo Methods and Applications, Vol. 19, No. 3, 01.10.2013, p. 237-259.

Research output: Contribution to journalArticle

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