淡江大學機構典藏:Item 987654321/110301
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62830/95882 (66%)
造访人次 : 4037460      在线人数 : 561
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/110301


    题名: Reducing Variance in Univariate Smoothing
    作者: Cheng, Ming-Yen;Peng, Liang;Wu, Jyh-Shyang
    关键词: Bandwidth;coverage probability;kernel;local linear regression;nonparametric smoothing;variance reduction
    日期: 2007-04-15
    上传时间: 2017-05-18 02:10:23 (UTC+8)
    摘要: A variance reduction technique in nonparametric smoothing is proposed: at each point of estimation, form a linear combination of a preliminary estimator evaluated at nearby points with the coefficients specified so that the asymptotic bias remains unchanged. The nearby points are chosen to maximize the variance reduction. We study in detail the case of univariate local linear regression. While the new estimator retains many advantages of the local linear estimator, it has appealing asymptotic relative efficiencies. Bandwidth selection rules are available by a simple constant factor adjustment of those for local linear estimation. A simulation study indicates that the finite sample relative efficiency often matches the asymptotic relative efficiency for moderate sample sizes. This technique is very general and has a wide range of applications.
    關聯: The Annals of Statistics 35(2), pp.522-542
    DOI: 10.1214/009053606000001398
    显示于类别:[數學學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML122检视/开启
    Reducing Variance in Univariate Smoothing.pdf292KbAdobe PDF1检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈