empiricallikelihoodbasedsubsetselectionforpartiallylinearautoregressivemodels
文献类型：期刊论文
| 作者 | Han Yu1; Jin Yinghua2; Chen Min2
|
| 刊名 | actamathematicaeapplicataesinica
 |
| 出版日期 | 2013 |
| 卷号 | 29期号:4页码:793 |
| ISSN号 | 0168-9673 |
| 英文摘要 | Based on the empirical likelihood method, the subset selection and hypothesis test for parameters in a partially linear autoregressive model are investigated. We show that the empirical log-likelihood ratio at the true parameters converges to the standard chi-square distribution. We then present the definitions of the empirical likelihood-based Bayes information criteria (EBIC) and Akaike information criteria (EAIC). The results show that EBIC is consistent at selecting subset variables while EAIC is not. Simulation studies demonstrate that the proposed empirical likelihood confidence regions have better coverage probabilities than the least square method, while EBIC has a higher chance to select the true model than EAIC. |
| 资助项目 | [National Natural Science Foundation of China] |
| 语种 | 英语 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/45178]  |
| 专题 | 应用数学研究所 |
| 作者单位 | 1.吉林大学 2.中国科学院数学与系统科学研究院 |
| 推荐引用方式 GB/T 7714 | Han Yu,Jin Yinghua,Chen Min. empiricallikelihoodbasedsubsetselectionforpartiallylinearautoregressivemodels[J]. actamathematicaeapplicataesinica,2013,29(4):793. |
| APA | Han Yu,Jin Yinghua,&Chen Min.(2013).empiricallikelihoodbasedsubsetselectionforpartiallylinearautoregressivemodels.actamathematicaeapplicataesinica,29(4),793. |
| MLA | Han Yu,et al."empiricallikelihoodbasedsubsetselectionforpartiallylinearautoregressivemodels".actamathematicaeapplicataesinica 29.4(2013):793. |
入库方式： OAI收割
来源：数学与系统科学研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。