Regressions Regularized by Correlations

被引：1
|
作者：
Lipovetsky, Stan [1 ]
机构：
[1] GfK North Amer, Minneapolis, MN 55427 USA
来源：
JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2018年 / 17卷 / 01期
关键词：
Multiple regression; multicollinearity; regularizations; robust solutions;
D O I：
10.22237/jmasm/1529506907
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：
The regularization of multiple regression by proportionality to correlations of predictors with dependent variable is applied to the least squares objective and normal equations to relax the exact equalities and to get a robust solution. This technique produces models not prone to multicollinearity and is very useful in practical applications.
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页数：15
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