Randomized quasi-Monte Carlo and Owen's boundary growth condition: A spectral analysis

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1. Verfasser: Liu, Yang
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Veröffentlicht: 2024
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_version_ 1866915290554564608
author Liu, Yang
author_facet Liu, Yang
contents In this work, we analyze the convergence rate of randomized quasi-Monte Carlo (RQMC) methods under Owen's boundary growth condition [Owen, 2006] via spectral analysis. Specifically, we examine the RQMC estimator variance for the two commonly studied sequences: the lattice rule and the Sobol' sequence, applying the Fourier transform and Walsh--Fourier transform, respectively, for this analysis. Assuming certain regularity conditions, our findings reveal that the asymptotic convergence rate of the RQMC estimator's variance closely aligns with the exponent specified in Owen's boundary growth condition for both sequence types. We also provide analysis for certain discontinuous integrands.
format Preprint
id arxiv_https___arxiv_org_abs_2405_05181
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Randomized quasi-Monte Carlo and Owen's boundary growth condition: A spectral analysis
Liu, Yang
Numerical Analysis
65C05
In this work, we analyze the convergence rate of randomized quasi-Monte Carlo (RQMC) methods under Owen's boundary growth condition [Owen, 2006] via spectral analysis. Specifically, we examine the RQMC estimator variance for the two commonly studied sequences: the lattice rule and the Sobol' sequence, applying the Fourier transform and Walsh--Fourier transform, respectively, for this analysis. Assuming certain regularity conditions, our findings reveal that the asymptotic convergence rate of the RQMC estimator's variance closely aligns with the exponent specified in Owen's boundary growth condition for both sequence types. We also provide analysis for certain discontinuous integrands.
title Randomized quasi-Monte Carlo and Owen's boundary growth condition: A spectral analysis
topic Numerical Analysis
65C05
url https://arxiv.org/abs/2405.05181