首页 | 本学科首页   官方微博 | 高级检索  
     


Unstructured principal fitted response reduction in multivariate regression
Authors:Jae Keun Yoo
Abstract:In this paper, an unstructured principal fitted response reduction approach is proposed. The new approach is mainly different from two existing model-based approaches, because a required condition is assumed in a covariance matrix of the responses instead of that of a random error. Also, it is invariant under one of popular ways of standardizing responses with its sample covariance equal to the identity matrix. According to numerical studies, the proposed approach yields more robust estimation than the two existing methods, in the sense that its asymptotic performances are not severely sensitive to various situations. So, it can be recommended that the proposed method should be used as a default model-based method.
Keywords:primary  62G08  secondary  62H05  Model-based reduction  Multivariate regression  Response dimension reduction  Sufficient dimension reduction
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号