UNIFORM ERROR BOUNDS FOR STOCHASTIC KRIGING

被引：3
|
作者：
Xie, Guangrui [1 ]
Chen, Xi [1 ]
机构：
[1] Virginia Tech, Grad Dept Ind & Syst Engn, 1145 Perry St, Blacksburg, VA 24061 USA
来源：
2020 WINTER SIMULATION CONFERENCE (WSC) | 2020年
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/WSC48552.2020.9384009
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, we propose an approach to construct uniform error bounds (or confidence intervals) for stochastic kriging with a prescribed confidence level. The theoretical development sheds some light on the impact of simulation experimental designs and budget allocation schemes as well as their relative importance on the large-sample properties of stochastic kriging. Through numerical evaluations, we demonstrate the superiority of the uniform error bounds to the simultaneous confidence intervals obtained by applying Bonferroni correction under various experimental settings.
引用
收藏
页码：361 / 372
页数：12
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