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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/62093


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    题名: Spatial Clusters in a Global-Dependence Model
    作者: 余清祥
    Wang, Tai-Chi;Yue,Ching-Syang Jack
    贡献者: 統計系
    关键词: Local Cluster;Spatial Global Dependence;Conditional Autocorrelated Regressive Model;Spatial Scan Statistic;EM Estimates;Generalized Least Square
    日期: 2013.04
    上传时间: 2013-12-03 18:16:10 (UTC+8)
    摘要: Spatial data often possess multiple components, such as local clusters and global clustering, and these effects are not easy to be separated. In this study, we propose an approach to deal with the cases where both global clustering and local clusters exist simultaneously. The proposed method is a two-stage approach, estimating the autocorrelation by an EM algorithm and detecting the clusters by a generalized least square method. It reduces the influence of global dependence on detecting local clusters and has lower false alarms. Simulations and the sudden infant disease syndrome data of North Carolina are used to illustrate the difference between the proposed method and the spatial scan statistic.
    關聯: Spatial and Spatio-temporal Epidemiology, 0,0
    数据类型: article
    DOI 連結: http://dx.doi.org/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] 期刊論文

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