English  |  正體中文  |  简体中文  |  Items with full text/Total items : 57023/90721 (63%)
Visitors : 12427833      Online Users : 55
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: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/20584

    Title: A brief review of shrinkage estimation of a multivariate normal mean with extension to multiple linear regression
    Authors: 林志娟;Lin, Jyh-jiuan;Pal, Nabendu;Chang, Ching-hui
    Contributors: 淡江大學統計學系
    Keywords: loss function;prediction mean squared error (PMSE);risk function
    Date: 2005-12
    Issue Date: 2009-11-30 12:52:41 (UTC+8)
    Publisher: Pushpa Publishing House
    Abstract: Estimation of regression coefficients in a linear regression model is essential not only to understand the relationship between the response (dependent) variable and the explanatory (independent) variables, but also for predicting the response variable efficiently. It is known that an improved shrinkage estimation of the regression coefficients leads to a better prediction of the response variable in terms of lower prediction mean squared error. In this review paper we revisit the shrinkage estimation of the regression coefficients, which is an extension of Stein�s seminal work on shrinkage estimation of a multivariate normal mean, and see its connection to prediction.
    We have compiled materials from the existing major works on shrinkage estimation and added some new results (or extended some existing less known results) so that our review paper gives a comprehensive idea of the topic and hence helps the researchers interested in this area.
    Relation: Advances and Applications in Statistics 5(3), pp.371-399
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

    Files in This Item:

    There are no files associated with this item.

    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