An Easy-to-Implement Hierarchical Standardization for Variable Selection under Strong Heredity Constraint.
An Easy-to-Implement Hierarchical Standardization for Variable Selection under Strong Heredity Constraint.
复制标题
强遗传约束下变量选择的易于实现的分层标准化。
DOI：
10.1007/s42519-020-00102-x
复制
发表时间：
2020
影响因子：
0.6
通讯作者：
Wang,Sijian
中科院分区：
文献类型：
--
作者：
Chen,Kedong;Li,William;Wang,Sijian
对于许多实际问题，回归模型遵循很强的遗传性(也称为边际性)，这意味着当存在二阶效应时，它们包含了双亲主效应。现有的方法大多依靠特殊惩罚函数或算法来增强变量选择的强遗传性。我们提出了一种新的分级标准化程序，以保持变量选择的强遗传性。我们的方法易于实现，适用于任何类型回归的任何变量选择方法。分级标准化的性能与常规标准化相当。我们还提供了稳健性检验和实际数据分析，以说明我们的方法的优点。
For many practical problems, the regression models follow the strong heredity property (also known as the marginality), which means they include parent main effects when a second-order effect is present. Existing methods rely mostly on special penalty functions or algorithms to enforce the strong heredity in variable selection. We propose a novel hierarchical standardization procedure to maintain strong heredity in variable selection. Our method is effortless to implement and is applicable to any variable selection method for any type of regression. The performance of the hierarchical standardization is comparable to that of the regular standardization. We also provide robustness checks and real data analysis to illustrate the merits of our method.