中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
postjtestinferenceinnonnestedlinearregressionmodels

文献类型:期刊论文

作者Chen Xinjie3; Fan Yanqin2; Wan Alan1; Zou Guohua3
刊名sciencechinamathematics
出版日期2015
卷号58期号:6页码:1203
ISSN号1674-7283
英文摘要This paper considers the post-J test inference in non-nested linear regression models. Post-J test inference means that the inference problem is considered by taking the first stage J test into account. We first propose a post-J test estimator and derive its asymptotic distribution. We then consider the test problem of the unknown parameters, and a Wald statistic based on the post-J test estimator is proposed. A simulation study shows that the proposed Wald statistic works perfectly as well as the two-stage test from the view of the empirical size and power in large-sample cases, and when the sample size is small, it is even better. As a result, the new Wald statistic can be used directly to test the hypotheses on the unknown parameters in non-nested linear regression models.
资助项目[General Research Fund from the Hong Kong Research Grants Council] ; [National Natural Science Foundation of China] ; [Hundred Talents Program of the Chinese Academy of Sciences]
语种英语
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/38036]  
专题中国科学院数学与系统科学研究院
作者单位1.香港城市大学
2.范德堡大学
3.中国科学院数学与系统科学研究院
推荐引用方式
GB/T 7714
Chen Xinjie,Fan Yanqin,Wan Alan,et al. postjtestinferenceinnonnestedlinearregressionmodels[J]. sciencechinamathematics,2015,58(6):1203.
APA Chen Xinjie,Fan Yanqin,Wan Alan,&Zou Guohua.(2015).postjtestinferenceinnonnestedlinearregressionmodels.sciencechinamathematics,58(6),1203.
MLA Chen Xinjie,et al."postjtestinferenceinnonnestedlinearregressionmodels".sciencechinamathematics 58.6(2015):1203.

入库方式: OAI收割

来源:数学与系统科学研究院

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