postjtestinferenceinnonnestedlinearregressionmodels

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	postjtestinferenceinnonnestedlinearregressionmodels
	Chen Xinjie 1; Fan Yanqin 2; Wan Alan 3; Zou Guohua 1
	2015
发表期刊	sciencechinamathematics
ISSN	1674-7283
卷号	58 期号:6 页码:1203
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.
语种	英语
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]
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/38037
专题	中国科学院数学与系统科学研究院
作者单位	1.中国科学院数学与系统科学研究院 2.范德堡大学 3.香港城市大学
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.