J4

• 数学 • 上一篇    下一篇

一个计算积分的替代抽样方法

胡果荣1,2, 史宁中2, 张宝学2   

  1. 1. 吉林大学 数学研究所, 长春 130012; 2. 东北师范大学 数学与统计学院, 长春 130024
  • 收稿日期:2005-10-27 修回日期:1900-01-01 出版日期:2006-05-26 发布日期:2006-05-26
  • 通讯作者: 胡果荣

An Alternative Algorithm for Estimating Integrals

HU Guo-rong1,2, SHI Ning-zhong2, ZHANG Bao-xue2   

  1. 1. Institute of Mathematics, Jilin University, Changchun 130012, China; 2. School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China
  • Received:2005-10-27 Revised:1900-01-01 Online:2006-05-26 Published:2006-05-26
  • Contact: HU Guo-rong

摘要: 为提高高维积分的计算速度, 提出一种替换Monte Carlo积分方法. 将积分区域以网格的形式离散化, 再在网格上以相应的密度函数之值为权函数采用离散的Gibbs抽样算法抽样, 对抽样得到的样本作均匀扰动后就可获得所需的新抽样序列,从而得到积分的近似估计值. 模拟表明新算法计算速度较快.

关键词: 模拟, 重要性抽样, Gibbs抽样, 格子点, 数值积分

Abstract: To enhance the computing speed of high dimensional integral, an alternative Monte Carlo sampling algorithm is proposed in this paper.Firstly, the integral region is partitioned into net form. Secondly, grid points are sampled by using discrete Gibbs sampling method whose weighted functions are values of corresponding density function. Lastly, a new sampling sequence will be obtained by adding an uniform variable sequence to the original sequence correspondingly, and an estimation of the integral is given. The new sampling algorithm is as simple as the traditional numerical method. Simulating output showed that the new algorithm performs very well in computing speed.

Key words: simulation, important sampling, Gibbs sampling, grid point, numerical integral

中图分类号: 

  • O212.4