Post-J test inference in non-nested linear regression models
文献类型：期刊论文
| 作者 | Chen XinJie2; Fan YanQin1; Wan Alan3; Zou GuoHua4 |
| 刊名 | SCIENCE CHINA-MATHEMATICS
 |
| 出版日期 | 2015 |
| 卷号 | 58期号:6页码:1203-1216 |
| 关键词 | DISTRIBUTIONS COEFFICIENTS VARIANCES EQUALITY non-nested linear regression post-J test Wald statistic |
| ISSN号 | 1674-7283 |
| 其他题名 | Post-J test inference in non-nested linear regression models |
| 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 |
| CSCD记录号 | CSCD:5444904 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/56109]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 作者单位 | 1.范德堡大学 2.中国科学院数学与系统科学研究院 3.伦敦城市大学 4.首都师范大学 |
| 推荐引用方式 GB/T 7714 | Chen XinJie,Fan YanQin,Wan Alan,et al. Post-J test inference in non-nested linear regression models[J]. SCIENCE CHINA-MATHEMATICS,2015,58(6):1203-1216. |
| APA | Chen XinJie,Fan YanQin,Wan Alan,&Zou GuoHua.(2015).Post-J test inference in non-nested linear regression models.SCIENCE CHINA-MATHEMATICS,58(6),1203-1216. |
| MLA | Chen XinJie,et al."Post-J test inference in non-nested linear regression models".SCIENCE CHINA-MATHEMATICS 58.6(2015):1203-1216. |
入库方式： OAI收割
来源：数学与系统科学研究院
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