Jackknifing the Ridge Regression Estimator: A Revisit

被引:20
|
作者
Khurana, Mansi [1 ]
Chaubey, Yogendra P. [2 ]
Chandra, Shalini [3 ]
机构
[1] Banasthali Univ, Dept Math & Stat, Jaipur, Rajasthan, India
[2] Concordia Univ, Dept Math & Stat, Montreal, PQ H3G 1M8, Canada
[3] Indian Stat Inst, Gauhati, Assam, India
基金
加拿大自然科学与工程研究理事会;
关键词
Multicollinearity; Ridge regression; Jackknife technique; PRIOR INFORMATION; BIAS;
D O I
10.1080/03610926.2012.729640
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Singh et al. (1986) proposed an almost unbiased ridge estimator using Jackknife method that required transformation of the regression parameters. This article shows that the same method can be used to derive the Jackknifed ridge estimator of the original (untransformed) parameter without transformation. This method also leads in deriving easily the second-order Jackknifed ridge that may reduce the bias further. We further investigate the performance of these estimators along with a recent method by Batah et al. (2008) called modified Jackknifed ridge theoretically as well as numerically.
引用
收藏
页码:5249 / 5262
页数:14
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