statisticalinferenceonseeminglyunrelatedsingleindexregressionmodels
文献类型：期刊论文
| 作者 | He Bing2; You Jinhong3; Chen Min1
|
| 刊名 | 应用数学学报
 |
| 出版日期 | 2016 |
| 卷号 | 32期号:4页码:945 |
| ISSN号 | 0168-9673 |
| 英文摘要 | In this article, we consider a class of seemingly unrelated single-index regression models. By taking the contemporaneous correlation among equations into account we construct the weighted estimators (WEs) for unknown parameters of the coefficients and the improved local polynomial estimators for the unknown functions, respectively. We establish the asymptotic normalities of these estimators, and show both of them are more asymptotically efficient than those ignoring the contemporaneous correlation. The performances of the proposed procedures are evaluated through simulation studies. |
| 语种 | 英语 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/46741]  |
| 专题 | 应用数学研究所 |
| 作者单位 | 1.中国科学院数学与系统科学研究院 2.School of Mathematics,Jilin University 3.School of Statistics and Management,Shanghai University of Finance and Economics |
| 推荐引用方式 GB/T 7714 | He Bing,You Jinhong,Chen Min. statisticalinferenceonseeminglyunrelatedsingleindexregressionmodels[J]. 应用数学学报,2016,32(4):945. |
| APA | He Bing,You Jinhong,&Chen Min.(2016).statisticalinferenceonseeminglyunrelatedsingleindexregressionmodels.应用数学学报,32(4),945. |
| MLA | He Bing,et al."statisticalinferenceonseeminglyunrelatedsingleindexregressionmodels".应用数学学报 32.4(2016):945. |
入库方式： OAI收割
来源：数学与系统科学研究院
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