中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Empirical likelihood for linear regression models under imputation for missing responses

文献类型:期刊论文

作者Wang, QH; Rao, JNK
刊名CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
出版日期2001-12-01
卷号29期号:4页码:597-608
关键词confidence intervals empirical likelihood linear regression imputation missing response regression parameters
ISSN号0319-5724
英文摘要The authors study the empirical likelihood method for linear regression models. They show that when missing responses are imputed using least squares predictors, the empirical log-likelihood ratio is asymptotically a weighted sum of chi-square variables with unknown weights. They obtain an adjusted empirical log-likelihood ratio which is asymptotically standard chi-square and hence can be used to construct confidence regions. They also obtain a bootstrap empirical log-likelihood ratio and use its distribution to approximate that of the empirical log-likelihood ratio. A simulation study indicates that the proposed methods are comparable in terms of coverage probabilities and average lengths of confidence intervals, and perform better than a normal approximation based method.
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000173921500005
出版者CANADIAN JOURNAL STATISTICS
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/16048]  
专题应用数学研究所
通讯作者Wang, QH
作者单位Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714
Wang, QH,Rao, JNK. Empirical likelihood for linear regression models under imputation for missing responses[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,2001,29(4):597-608.
APA Wang, QH,&Rao, JNK.(2001).Empirical likelihood for linear regression models under imputation for missing responses.CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,29(4),597-608.
MLA Wang, QH,et al."Empirical likelihood for linear regression models under imputation for missing responses".CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 29.4(2001):597-608.

入库方式: OAI收割

来源:数学与系统科学研究院

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