Two-parameter ridge estimation in seemingly unrelated regression models

被引:2
|
作者
Esfanjani, Robab Mehdizadeh [1 ,2 ]
Najarzadeh, Dariush [3 ]
Khamnei, Hossein Jabbari [3 ]
Hormozinejad, Farshin [2 ]
Talebi, Mahnaz [4 ]
机构
[1] Islamic Azad Univ, Khouzestan Sci & Res Branch, Dept Stat, Ahvaz, Iran
[2] Islamic Azad Univ, Dept Stat, Ahvaz, Iran
[3] Univ Tabriz, Fac Math Sci, Dept Stat, Tabriz, Iran
[4] Tabriz Univ Med Sci, Neurosci Res Ctr, Tabriz, Iran
关键词
Multicollinearity; One-parameter ridge solution; Seemingly unrelated regression models; Two-parameter ridge solution; BIASED-ESTIMATION; SYSTEM; COMPLICATIONS;
D O I
10.1080/03610918.2020.1749662
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
Seemingly unrelated regression (SUR) models were applied when several linear regression equations were investigated at the same time. To reduce the multicollinearity influence in the SUR models, the one-parameter ridge (Ridge-1) solution was proposed and discussed by some researchers. As a generalization of the Ridge-1 solution, in the context of SUR models having multicollinearity problem, the two-parameter ridge (Ridge-2) solution was presented. Some simulations were performed to compare the proposed solution with the ordinary generalized least squares (GLS) and Ridge-1 solutions. Lastly, the proposed solution was applied on chronic renal failure effect data.
引用
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页码:4904 / 4918
页数:15
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