A practical approach to the error estimation of quasi-Monte Carlo integrations

被引:0
|
作者
Morohosi, H [1 ]
Fushimi, H [1 ]
机构
[1] Univ Tokyo, Grad Sch Engn, Bunkyo Ku, Tokyo 1138656, Japan
关键词
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
There have been few studies on practical error estimation methods of quasi-Monte Carlo integrations. Recently, some theoretical works were developed by Owen to analyze the quasi-Monte Carlo integration error. However his method given by those works is complicated to be implemented and needs huge computational efforts, so it would be of some interest to investigate into a simple error estimation method. In this paper, we will use a simple method, and give some theoretical considerations on the errors given by these two methods. Numerical experiments are also reported.
引用
收藏
页码:377 / 390
页数:14
相关论文
共 50 条
  • [1] On quasi-Monte Carlo integrations
    Sobol, IM
    [J]. MATHEMATICS AND COMPUTERS IN SIMULATION, 1998, 47 (2-5) : 103 - 112
  • [2] Error in Monte Carlo, quasi-error in Quasi-Monte Carlo
    Kleiss, Ronald
    Lazopoulos, Achilleas
    [J]. COMPUTER PHYSICS COMMUNICATIONS, 2006, 175 (02) : 93 - 115
  • [3] Density Estimation by Monte Carlo and Quasi-Monte Carlo
    L'Ecuyer, Pierre
    Puchhammer, Florian
    [J]. MONTE CARLO AND QUASI-MONTE CARLO METHODS, MCQMC 2020, 2022, 387 : 3 - 21
  • [4] Error estimates in Monte Carlo and Quasi-Monte Carlo integration
    Lazopouls, A
    [J]. ACTA PHYSICA POLONICA B, 2004, 35 (11): : 2617 - 2632
  • [5] Monte Carlo, quasi-Monte Carlo, and randomized quasi-Monte Carlo
    Owen, AB
    [J]. MONTE CARLO AND QUASI-MONTE CARLO METHODS 1998, 2000, : 86 - 97
  • [6] Error trends in Quasi-Monte Carlo integration
    Schlier, C
    [J]. COMPUTER PHYSICS COMMUNICATIONS, 2004, 159 (02) : 93 - 105
  • [7] RANDOMIZED QUASI-MONTE CARLO FOR QUANTILE ESTIMATION
    Kaplan, Zachary T.
    Li, Yajuan
    Nakayama, Marvin K.
    Tuffin, Bruno
    [J]. 2019 WINTER SIMULATION CONFERENCE (WSC), 2019, : 428 - 439
  • [8] Monte Carlo and Quasi-Monte Carlo Density Estimation via Conditioning
    L'Ecuyer, Pierre
    Puchhammer, Florian
    Ben Abdellah, Amal
    [J]. INFORMS JOURNAL ON COMPUTING, 2022, 34 (03) : 1729 - 1748
  • [9] Density Estimation by Randomized Quasi-Monte Carlo
    Abdellah, Amal Ben
    L'Ecuyer, Pierre
    Owen, Art B.
    Puchhammer, Florian
    [J]. SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2021, 9 (01): : 280 - 301
  • [10] Accuracy estimation for quasi-Monte Carlo simulations
    Snyder, WC
    [J]. MATHEMATICS AND COMPUTERS IN SIMULATION, 2000, 54 (1-3) : 131 - 143