English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62805/95882 (66%)
造访人次 : 3865056      在线人数 : 191
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/987654321/18490

    题名: Fuzzy-weighted bootstrap estimation in semi-parametric model
    作者: Tsai, Tzong-ru;Wu, Shuo-jye
    贡献者: 淡江大學統計學系
    关键词: Bootstrap estimation;optimal fuzzy clustering analysis method;ordinary least squares estimation;percentile interval estimation;semi-parametric model
    日期: 2003-06-14
    上传时间: 2009-09-01 16:09:12 (UTC+8)
    出版者: TARU Publications
    摘要: Many statisticians use a semi-parametric model to examine the relationship between explanatory and response variables. In practice, a data set often contains outliers and, hence the traditional estimation methods may not be appropriate. Wu et al. (1996) provided a fuzzy-weighted estimator to reduce the influence of outliers and they discussed its asymptotic properties. However, the test performance in small sample is not discussed. In this paper, a percentile interval estimation method based on fuzzy-weighted bootstrap samples is provided and we call the improved percentile interval estimation method. We show that the fuzzy-weighted bootstrap estimator and the fuzzy-weighted estimator have the same asymptotic properties. In addition, the proposed method can reduce the influence of outliers efficiently when we make inference about the scaled regression coefficient in small sample. Hence, we provide an alternative estimation method to make inference when sample size is small.
    關聯: Journal of statistics and management systems 6(3), p.443-461
    DOI: 10.1080/09720510.2003.10701092
    显示于类别:[統計學系暨研究所] 期刊論文


    档案 大小格式浏览次数



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