淡江大學機構典藏:Item 987654321/75095
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62805/95882 (66%)
Visitors : 3943752      Online Users : 688
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
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/75095


    Title: SAS macro programs for geographically weighted generalized linear modeling with spatial point data: Applications to health research
    Authors: Chen, Vivian Yi-Ju;Yang, Tse-Chuan
    Contributors: 淡江大學統計學系
    Keywords: SAS;Geographically weighted generalized linear modeling;Geographically weighted regression;Spatial point data;Spatial non-stationarity
    Date: 2012-08-01
    Issue Date: 2012-03-12 17:41:02 (UTC+8)
    Publisher: Shannon: Elsevier Ireland Ltd.
    Abstract: An increasing interest in exploring spatial non-stationarity has generated several specialized analytic software programs; however, few of these programs can be integrated natively into a well-developed statistical environment such as SAS. We not only developed a set of SAS macro programs to fill this gap, but also expanded the geographically weighted generalized linear modeling (GWGLM) by integrating the strengths of SAS into the GWGLM framework. Three features distinguish our work. First, the macro programs of this study provide more kernel weighting functions than the existing programs. Second, with our codes the users are able to better specify the bandwidth selection process compared to the capabilities of existing programs. Third, the development of the macro programs is fully embedded in the SAS environment, providing great potential for future exploration of complicated spatially varying coefficient models in other disciplines. We provided three empirical examples to illustrate the use of the SAS macro programs and demonstrated the advantages explained above.
    Relation: Computer Methods and Programs in Biomedicine 107(2), pp.262–273
    DOI: 10.1016/j.cmpb.2011.10.006
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML87View/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