中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Probability density estimation with data missing at random when covariables are present

文献类型:期刊论文

作者Wang, Qihua1,2
刊名JOURNAL OF STATISTICAL PLANNING AND INFERENCE
出版日期2008-03-01
卷号138期号:3页码:568-587
关键词inverse probability weighted method asymptotic normality mean squared error bound
ISSN号0378-3758
DOI10.1016/j.jspi.2006.10.017
英文摘要This paper addresses the problem of the probability density estimation in the presence of covariates when data are missing at random (MAR). The inverse probability weighted method is used to define a nonparametric and a semiparametric weighted probability density estimators. A regression calibration technique is also used to define an imputed estimator. It is shown that all the estimators are asymptotically normal with the same asymptotic variance as that of the inverse probability weighted estimator with known selection probability function and weights. Also, we establish the mean squared error (MSE) bounds and obtain the MSE convergence rates. A simulation is carried out to assess the proposed estimators in terms of the bias and standard error. (C) 2007 Elsevier B.V. All rights reserved.
语种英语
WOS记录号WOS:000253099800003
出版者ELSEVIER SCIENCE BV
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/5766]  
专题应用数学研究所
通讯作者Wang, Qihua
作者单位1.Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式
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Wang, Qihua. Probability density estimation with data missing at random when covariables are present[J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE,2008,138(3):568-587.
APA Wang, Qihua.(2008).Probability density estimation with data missing at random when covariables are present.JOURNAL OF STATISTICAL PLANNING AND INFERENCE,138(3),568-587.
MLA Wang, Qihua."Probability density estimation with data missing at random when covariables are present".JOURNAL OF STATISTICAL PLANNING AND INFERENCE 138.3(2008):568-587.

入库方式: OAI收割

来源:数学与系统科学研究院

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