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摘要: |
本文研究了高维线性模型的变量选择和参数估计问题,
提出了广义SELO惩罚函数族, 推广了SELO惩罚回归方法.
模拟研究和实际数据分析评估了提出方法在有限样本下的表现. |
关键词: 坐标下降 高维BIC 局部线性逼近 惩罚最小二乘 SELO惩罚 |
DOI: |
分类号:O212.1 |
基金项目:国家自然科学基金(11501579; 41572315);中国地质大学(武汉)中央高校基本科研业务费专项资金(CUGW150809) |
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High-dimensional variable selection via generalized SELO-penalized linear regression |
SHI YUE YONG,JIAO YU LING
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Abstract: |
This paper studies the problem of variable selection and parameter estimation
in high-dimensional linear models,
presents a generalized SELO penalty function family
and extends the SELO-penalized regression method to a more general framework.
Simulation studies and a real data analysis are conducted to assess the finite sample performance of the proposed method. |
Key words: coordinate descent high-dimensional BIC local linear approximation penalized least squares SELO penalty |