 English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 58323/91876 (63%) 造访人次 : 14053590      在线人数 : 49
 RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
 搜寻范围 全部機構典藏 商管學院    統計學系暨研究所       --期刊論文 查询小技巧：您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据 进阶搜寻
 主页 ‧ 登入 ‧ 上传 ‧ 说明 ‧ 关于機構典藏 ‧ 管理 淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 >  Item 987654321/69215

 jsp.display-item.identifier=請使用永久網址來引用或連結此文件: `http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/69215`

 题名: On study of kernel regression function polygons 作者: 鄧文舜;Deng, Wen-shuenn;Chu, C.K. 贡献者: 淡江大學統計學系 日期: 2000-01-01 上传时间: 2011-10-23 16:37:42 (UTC+8) 摘要: In the case of the random design nonparametric regression, the regression function estimate is produced practically by joining every two consecutive kernel estimates of regression function values by a straight line segment. Hence, it is of polygon type, and is called the kernel regression function polygon (KRFP) in this paper. The KRFP is analyzed by its asymptotic integrated mean square error (AIMSE). This AIMSE precisely quantifies both effects of the kernel function and of the distance between the points on which kernel estimates of regression function values are calculated on the KRFP. By studying the AIMSE, we have the following findings. First of all, if the distance is of smaller order in magnitude than the bandwidth used by the kernel regression function estimator, then Epanechnikov kernel is still the optimal kernel function for the KRFP. Secondly, if the distance is of the same order in magnitude as the bandwidth, then Epanechnikov kernel is no longer optimal for the KRFP. In this case, using the AIMSE of the KRFP, we obtain the optimal kernel for the KRFP over the class of two-degree polynomials by numerical calculation. As the distance increases, the computation time of the KRFP decreases. However, the resulting performance of the KRFP deteriorates, since the minimum AIMSE of the KRFP over both the bandwidth and the kernel function increases. Finally, if the distance is of larger order in magnitude than the bandwidth, then the uniform kernel is the optimal kernel function for the KRFP. 關聯: Journal of nonparametric statistics 12(5), pp.597-609 DOI: 10.1080/10485250008832824 显示于类别: [統計學系暨研究所] 期刊論文

index.html0KbHTML5检视/开启

 TAIR相关文章

 DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈