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    题名: 空間自相關模型下空間群聚檢定
    Spatial Clusters in a Global-dependence Model
    作者: 王泰期
    Wang, Tai Chi
    贡献者: 余清祥
    王泰期
    Wang, Tai Chi
    关键词: 群聚偵測
    空間自相關
    空間掃描統計量
    空間自相關模型
    EM演算法
    日期: 2012
    上传时间: 2013-09-02 15:35:34 (UTC+8)
    摘要: 因為疾病空間模式通常會與環境中的危險因子有很強烈的關聯性，因此流行病學家與社會大眾都對疾病的空間模式感到興趣。舉例來說，空間群聚就是一項非常受到重視的疾病空間模式，在眾多的空間群聚檢定方法種，Kulldorff和 Nagarwalla在1995年提出的空間掃描統計量是相當受到廣泛應用的方法，雖然這個統計方法可以檢定初空間資料的異質性，但是卻沒有辦法區隔這些異質性是來自於整體空間資料的相關性或是局部的空間群聚。在本篇論文中，我們將分別提出計次型的統計方法與貝氏統計方法兩種類型的空間群聚檢定方法來處理這樣的問題，其中計次型的統計方法為一兩階段的統計方法，首先採用EM演算法來估計空間自相關，並根據估計的結果與掃描窗格在偵測空間群聚；另一方面，貝氏方法則考慮加入群聚的中心位置及半徑作為事前的機率分布，進而透過MCMC的方法來計算出後驗分布的結果。除此之外，北卡羅來納的嬰兒猝死症和台灣老年人口癌症死亡資料將被用來示範與評價不同群聚檢定方法的差異與效果。
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    描述: 博士
    國立政治大學
    統計研究所
    95354504
    101
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0095354504
    数据类型: thesis
    DOI 連結: http://dx.doi.org/10.1016/j.sste.2013.03.003
    DOI: 10.1016/j.sste.2013.03.003
    显示于类别:[統計學系] 學位論文

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