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請使用永久網址來引用或連結此文件:
http://ir.ncue.edu.tw/ir/handle/987654321/14055
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題名: | 空間迴歸模型變數選取方法(1/2) Variable Selection for Spatial Regression Models |
作者: | 陳春樹 |
貢獻者: | 統計資訊研究所 |
關鍵詞: | Conditional information criterion;Data perturbation;Spatial prediction;Stabilization;Stein’s unbiased risk estimate;Variable selection. |
日期: | 2009
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上傳時間: | 2012-09-10T04:40:17Z
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出版者: | 行政院國家科學委員會 |
摘要: | Variable selection in geostatistical regression is an important problem, but has not been well studied in the literature. In the first year of this project, we focus on spatial prediction and consider a class of conditional information criteria indexed by a penalty parameter. Instead of directly applying a criterion, which leads to a discontinuous spatial predictor with respect to the response variables, we further stabilize the predictor by local model averaging, resulting in a predictor that is not only continuous but also differentiable. Then Stein’s unbiased risk estimate is applied to select the penalty parameter, which takes estimation of model parameters into account and can be computed using a simple Monte Carlo method. In the second year of this project, we will continue to complete the expected goals. |
關聯: | 國科會計畫, 計畫編號: NSC98-2118-M018-003-MY2; 研究期間: 9808-9907 |
顯示於類別: | [統計資訊研究所] 國科會計畫
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2020800312001.pdf | 93Kb | Adobe PDF | 440 | 檢視/開啟 |
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