淡江大學機構典藏:Item 987654321/120279
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 60932/93628 (65%)
造訪人次 : 1252334      線上人數 : 11
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/120279


    題名: On the Use of Geographically Weighted Count Models
    作者: Chen, Vivian Yi-Ju
    關鍵詞: Spatial nonstationarity;Geographically weighted regression;Count data;Overdispersion;Zero inflation
    日期: 2020-08-20
    上傳時間: 2021-03-19 12:11:23 (UTC+8)
    摘要: The past years have experienced growth in the methodological development that
    intend to explore spatial nonsationarity for spatially count data based on the technique of geographically weighted regression. Several geographically weighted count models have been introduced in literature to deal with the challenges of analyzing the count data without/with overdispersion and/or excessive zeros. However, researchers have lagged to provide a comparative assessment across all the proposed methods. In this study, we argue that spatial analysts should pay sufficient attention to analytical model comparisons since different geographically weighted count models may generate competing accounts of the same data set. Here we first review the existing techniques and introduce geographically weighted zero-inflated negative binomial model as a methodological complement. Several qualitative measures and graphical tools are then suggested to compare among various GW count models. We also illustrate their utility using an example from a study of Taiwan dengue data. The results demonstrate the importance of model comparisons in investigating spatial nonstationarity for spatial count data analyses.
    關聯: 第二十九屆南區統計研討會
    顯示於類別:[統計學系暨研究所] 會議論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML54檢視/開啟
    第二十九屆南區統計研討會_議程表.pdf650KbAdobe PDF65檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

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