English  |  正體中文  |  简体中文  |  Items with full text/Total items : 52359/87459 (60%)
Visitors : 9139776      Online Users : 252
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/987654321/97105

    Authors: Lin, Kuo-Chin;Chen, Yi-Ju
    Contributors: 淡江大學統計學系
    Date: 2012-08
    Issue Date: 2014-03-17 10:41:12 (UTC+8)
    Publisher: Kumamoto: ICIC International
    Abstract: A nonparametric smoothing method for assessing the adequacy of generalized linear mixed models (GLMMs) is developed. The proposed method is based on smoothing the residuals over continuous covariates to avoid the partition of continuous covariates on model checking. The global test statistic has a quadratic form and its formulae of expectation as well as variance are derived. The sampling distribution of the quadratic form test statistic is approximated by a scaled chi-squared distribution. For bandwidth selection, the leave-one-out cross-validation approach is recommendable for use. A longitudinal binary data set is utilized to demonstrate the proposed approach.
    Relation: International Journal of Innovative Computing, Information and Control 8(8), pp.5693-5701
    Appears in Collections:[統計學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    1349-4198_8(8)p5693-5701.pdf97KbAdobe PDF166View/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