English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62637/95499 (66%)
Visitors : 3032913      Online Users : 411
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/987654321/20602

    Title: An optimal test for the mean function hypothesis
    Authors: Chang, K. F.;吳忠武;Wu, Jong-wuu
    Contributors: 淡江大學統計學系
    Keywords: Consistency;estimation equation;goodness of fit;mean function;pitman efficiency
    Date: 1998-01-01
    Issue Date: 2009-11-30 12:53:23 (UTC+8)
    Publisher: Statistica Sinica
    Abstract: The conditional mean of the response variable Y ggiven the covariates is usually modelle d by a parametric function g(βx), where g(.) is a known function and β is a row vector of p unknown parameters. In this paper, a new method for testing the goodness of fit of the model g(βx) for the mean function is presented. The new test depends on the selection of weight functions. An expression for the efficacy of the proposed test under a sequence of local alternatives will be given. With the application of this result one can direct the choice of the optimal weight functions in order to maximize the efficacy. The new test is simple in computation and consistent against a broad class of alternatives. Asymptotically, the null distribution is independent of the underlying distribution of Y given X=x. Two pratical examples are given to illustrate the method. Further, simulation studies are given to show the advantages of the proposed test.
    Relation: Statistica sinica 8, pp.477-487
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

    Files in This Item:

    File Description SizeFormat
    An optimal test for the mean function hypothesis.pdf590KbAdobe PDF1View/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