淡江大學機構典藏:Item 987654321/20622
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62819/95882 (66%)
Visitors : 4002822      Online Users : 690
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20622


    Title: The local linear M-estimator with a robust initial estimate
    Authors: Hwang, Ruey-ching;鄧文舜;Deng, Wen-shuenn;Chu, Chih-kang
    Contributors: 淡江大學統計學系
    Keywords: local linear estimator;local linear M-estimator;Newton method;nonparametric regression;robust initial estimate;robustness
    Date: 2006-12-01
    Issue Date: 2009-11-30 12:54:02 (UTC+8)
    Publisher: 中國統計學社
    Abstract: In the field of nonparametric regression, the local linear M-estimator (LLM; Fan and Jiang 1999) is proposed to adjust for the unrobustness of the local linear estimator (LLE; Fan 1992, 1993). In practice, the LLM is often computed using Newton method together with an initial estimate produced by the LLE. However, by the unrobustness of the LLE, such initial estimate might be far from the global minimizer of M function. In this case, the Newton method might provide an incorrect solution for the LLM. To improve the drawback, a robust initial estimate for Newton method is proposed. Simulation results show that our robust initial estimate is useful when using Newton method to find a solution for the LLM.
    Relation: 中國統計學報 44(4),頁 382-401
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML181View/Open
    The local linear M-estimator with a robust initial estimate.pdf1615KbAdobe PDF0View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


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