中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Non-parametric method for filling in the missing value for cross-sectional dataset: A validation on the per capita GDP data at county level in China

文献类型:期刊论文

作者Deng, XZ ; yin,Fang(殷芳) ; Lin, YZ ; Yuan, YW
刊名JOURNAL OF FOOD AGRICULTURE & ENVIRONMENT
出版日期2012
卷号10期号:3-4页码:1350-1354
关键词Non-parametric method stepwise multiple regression interpolation per capita GDP China
通讯作者Deng, XZ
英文摘要When dealing with the observation with missing values, we used to get them by means of mathematical interpolation. Compared with the traditional methods for parametric interpolation including linear interpolation, spline interpolation, kriging interpolation, etc., which sometimes export so paradoxical results that there are quite a lot of debates on the reliability of rationale and application, the non-parametric methods are becoming more and more popular to interpolate the missing values for the cross sectional dataset. In this paper, a non-parametric method is introduced and its feasibility of filling in missing values of per capita GDP data at county level for China is illustrated and verified. The results indicate that the non-parametric method produces essentially unbiased estimates by using kernel density function based on a sample drawn from all the observations. So it appears that the actual performance of non-parametric model can be quite helpful to fill in the missing values with a large sample of observation and the non-parametric extrapolation methods tested in this empirical study could be applied in other similar studies
收录类别SCI
资助信息National Basic Research Program of China 2012CB95570001 2010CB950904;National Science Foundation of China 40801231 41071343 41171434 70873118;National Soft Science Research Program of China 2010GXS5B163
公开日期2013-04-23
源URL[http://ir.igsnrr.ac.cn/handle/311030/27863]  
专题地理科学与资源研究所_研究生部
推荐引用方式
GB/T 7714
Deng, XZ,yin,Fang,Lin, YZ,et al. Non-parametric method for filling in the missing value for cross-sectional dataset: A validation on the per capita GDP data at county level in China[J]. JOURNAL OF FOOD AGRICULTURE & ENVIRONMENT,2012,10(3-4):1350-1354.
APA Deng, XZ,yin,Fang,Lin, YZ,&Yuan, YW.(2012).Non-parametric method for filling in the missing value for cross-sectional dataset: A validation on the per capita GDP data at county level in China.JOURNAL OF FOOD AGRICULTURE & ENVIRONMENT,10(3-4),1350-1354.
MLA Deng, XZ,et al."Non-parametric method for filling in the missing value for cross-sectional dataset: A validation on the per capita GDP data at county level in China".JOURNAL OF FOOD AGRICULTURE & ENVIRONMENT 10.3-4(2012):1350-1354.

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来源:地理科学与资源研究所

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