關鍵字查詢 | 類別:會議論文 | | 關鍵字:Spatial-Temporal Model for Count Data

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序號 學年期 教師動態
1 103/2 統計系 張雅梅 副教授 會議論文 發佈 Spatial-Temporal Model for Count Data , [103-2] :Spatial-Temporal Model for Count Data會議論文Spatial-Temporal Model for Count DataYa-Mei ChangPoisson-lognormal model;Spatial-temporal process;Disease maps;Lasso;group Lasso第二十四屆南區統計研討會暨2015中華機率統計學會年會及學術研討會In epidemiology, disease mapping using count data is a very important issue. Under a Poisson-lognormal model, we develop a spatial-temporal process. The log transformation of the conditional expected number of cases is decomposed as a linear combination of basis functions and a stationary process. The problem of mean and covariance estimations can be considered as a regression. A subset selection method of Lasso and group Lasso are used to choose a suitable subset of the basis functions and estimate the mean and covariances. This method can characterize either non-stationary or nearly stationary spatial processes, and is computationally efficient for large data sets.zh_TW國內無20150627~20150628否TWN第二十四屆南區統計研討會暨2015中華機率統計學會年會及學術研討會國立彰化師範大學進德校區, 彰化, 台灣
2 102/2 統計系 張雅梅 副教授 會議論文 發佈 Spatial-Temporal Model for Count Data , [102-2] :Spatial-Temporal Model for Count Data會議論文Spatial-Temporal Model for Count Data張雅梅淡江大學統計學系2014年智慧科技與應用統計研討會銘傳大學tku_id: 000140248;Submitted by 雅梅 張 (140248@mail.tku.edu.tw) on 2014-10-24T08:14:25Z No. of bitstreams: 0;Made available in DSpace on 2014-10-24T08:14:25Z (GMT). No. of bitstreams: 0zh_TW國內20140524TWN臺北市, 臺灣<links><record><name>機構典藏連結</name><url>http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99305</url></record></links>
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