Improved bounds on the gain coefficients for digital nets in prime power base
Improved bounds on the gain coefficients for digital nets in prime power base
复制标题
改进了主功率基础中数字网络增益系数的界限
DOI:
10.1016/j.jco.2022.101722
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发表时间:
2023
影响因子:
1.7
通讯作者:
Kosuke Suzuki
中科院分区:
文献类型:
--
作者:
Takashi Goda;Kosuke Suzuki
We study randomized quasi-Monte Carlo integration by scrambled nets. The scrambled net quadrature has long gained its popularity because it is an unbiased estimator of the true integral, allows for a practical error estimation, achieves a high order decay of the variance for smooth functions, and works even for L p-functions with any p≥ 1. The variance of the scrambled net quadrature for L 2-functions can be evaluated through the set of the so-called gain coefficients. In this paper, based on the system of Walsh functions and the concept of dual nets, we provide improved upper bounds on the gain coefficients for digital nets in general prime power base. Our results explain the known bound by Owen (1997) for Faure sequences, the recently improved bound by Pan and Owen (2022) for digital nets in base 2 (including Sobol'sequences as a special case), and their finding that all the nonzero gain coefficients for digital nets in base 2 must be powers of two, all in a unified way.
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影响因子:
0.7
作者:
H. Niederreiter;G. Pirsic
通讯作者:
G. Pirsic
DOI:
10.1016/j.jco.2022.101700
发表时间:
2021
期刊:
J. Complex.
影响因子:
--
作者:
Z. Pan;A. Owen
通讯作者:
A. Owen
影响因子:
0.8
作者:
R. Yue;S. Mao
通讯作者:
R. Yue;S. Mao
影响因子:
1.7
作者:
Julian Hofstadler;Daniel Rudolf
通讯作者:
Daniel Rudolf