Geostatistical model averaging based on conditional information criteria

NCU Institutional Repository > 理學院 > 統計研究所 > 期刊論文 > Item 987654321/105807

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/105807

题名:	Geostatistical model averaging based on conditional information criteria
作者:	陳春樹;Chen, Chun-Shu;Huang, Hsin-Cheng
贡献者:	理學院統計研究所
关键词:	Biomedical and Life Sciences;Chemical contaminants;Chemistry and Earth Sciences;Computer Science;Criteria;data collection;Ecology;Environmental monitoring;Geostatistics;Health Sciences;Lakes;Life Sciences;Maine;Math. Appl. in Environmental Science;Mathematical analysis;Mathematical models;Medicine;Mercury;Physics;prediction;Regression;risk estimate;selection methods;Statistics;Statistics for Engineering;Statistics for Life Sciences;Studies;Theoretical Ecology/Statistics;Variables;Water pollution
日期:	2012-03-01
上传时间:	2026-04-23 12:53:33 (UTC+8)
出版者:	Springer Netherlands;Boston: Springer-Verlag
摘要:	摘要： Variable selection in geostatistical regression is an important problem, but has not been well studied in the literature. In this paper, we focus on spatial prediction and consider a class of conditional information criteria indexed by a penalty parameter. Instead of applying a fixed criterion, which leads to an unstable predictor in the sense that it is discontinuous with respect to the response variables due to that a small change in the response may cause a different model to be selected, we further stabilize the predictor by local model averaging, resulting in a predictor that is not only continuous but also differentiable even after plugging-in estimated model parameters. Then Stein’s unbiased risk estimate is applied to select the penalty parameter, leading to a data-dependent penalty that is adaptive to the underlying model. Some numerical experiments show superiority of the proposed model averaging method over some commonly used variable selection methods. In addition, the proposed method is applied to a mercury data set for lakes in Maine. 其他題名： Environ Ecol Stat 出版者： Boston: Springer-Verlag 出版日期： 2012-03-01 出處： Environmental and ecological statistics, 2012-03, Vol.19 (1), p.23-35 資源來源： Agricultural & Environmental Science Collection 版權： Springer Science+Business Media, LLC 2011 版權： Springer Science+Business Media, LLC 2012 識別號： ISSN: 1352-8505 識別號： EISSN: 1573-3009 識別號： DOI: 10.1007/s10651-011-0171-2
显示于类别:	[統計研究所] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	17	检视/开启

在NCUIR中所有的数据项都受到原著作权保护.

社群 sharing

数据加载中.....