Quasi-Monte Carlo Software
Mathematical Software
2021-10-15 v3 Numerical Analysis
Numerical Analysis
Abstract
Practitioners wishing to experience the efficiency gains from using low discrepancy sequences need correct, robust, well-written software. This article, based on our MCQMC 2020 tutorial, describes some of the better quasi-Monte Carlo (QMC) software available. We highlight the key software components required by QMC to approximate multivariate integrals or expectations of functions of vector random variables. We have combined these components in QMCPy, a Python open-source library, which we hope will draw the support of the QMC community. Here we introduce QMCPy.
Keywords
Cite
@article{arxiv.2102.07833,
title = {Quasi-Monte Carlo Software},
author = {Sou-Cheng T. Choi and Fred J. Hickernell and R. Jagadeeswaran and Michael J. McCourt and Aleksei G. Sorokin},
journal= {arXiv preprint arXiv:2102.07833},
year = {2021}
}
Comments
25 pages, 7 figures, to be published in the MCQMC2020 Proceedings