# 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 language English 237-259 23 Monte Carlo Methods and Applications 19 3 https://doi.org/10.1515/mcma-2013-0012 Published - 2013 Oct 1

### Fingerprint

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

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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