A Random Number Generator for the Kolmogorov Distribution
Computation
2022-08-30 v1 Probability
Abstract
We discuss an acceptance-rejection algorithm for the random number generation from the Kolmogorov distribution. Since the cumulative distribution function (CDF) is expressed as a series, in order to obtain the density function we need to prove that the series of the derivatives converges uniformly. We also provide a similar proof in order to show that the ratio between the target Kolmogorov density and the auxiliary density implemented is bounded. Finally we discuss a way of truncating the series expression of the density in an optimal way.
Cite
@article{arxiv.2208.13598,
title = {A Random Number Generator for the Kolmogorov Distribution},
author = {Paolo Onorati and Brunero Liseo},
journal= {arXiv preprint arXiv:2208.13598},
year = {2022}
}