Importance Sampling Based on the Kernel Density Estimator

摘要：

　　Importance Sampling is an unbiased sampling method used to sample random variables form different densities than originally defined.The importance sampling densities should be constructed to pick up important random variables to improve the estimation of a interesting statistics.In this article, we present an importance sampling in which its density function is constructed from the kernel density estimators.This method can generate a sufficient number of samples, and then increase the accuracy of the probability estimate.

关键词： Kernel Density Estimator Importance Sampling

作者: XueGao Zhang

作者单位: Department of Business Administration,Yunnan Normal University Business School No.1 Business School Road,Kunming High-tech Zone Kunming,China

会议类型: 国际会议

会议名称: 2013 International Conference on Education Technology and Management Science(ICETMS2013)2013年教育技术与管理科学国际会议

会议地点: 南京

会议语种:英文

页码: 206-208

在线出版日期: 2013-06-08（万方平台首次上网日期，不代表论文的发表时间）