Digital Nets and Sequences for Quasi-Monte Carlo Methods
Numerical Analysis
2022-07-29 v1 Mathematical Software
Numerical Analysis
Abstract
Quasi-Monte Carlo methods are a way of improving the efficiency of Monte Carlo methods. Digital nets and sequences are one of the low discrepancy point sets used in quasi-Monte Carlo methods. This thesis presents the three new results pertaining to digital nets and sequences: implementing randomized digital nets, finding the distribution of the discrepancy of scrambled digital nets, and obtaining better quality of digital nets through evolutionary computation. Finally, applications of scrambled and non-scrambled digital nets are provided.
Keywords
Cite
@article{arxiv.2207.13802,
title = {Digital Nets and Sequences for Quasi-Monte Carlo Methods},
author = {Hee Sun Hong},
journal= {arXiv preprint arXiv:2207.13802},
year = {2022}
}