论文标题
在强遗传约束下，用于可变选择的易于实施的层次标准化
An Easy-to-Implement Hierarchical Standardization for Variable Selection Under Strong Heredity Constraint
论文作者
论文摘要
对于许多实际问题，回归模型遵循强大的遗传特性（也称为边缘性），这意味着当存在二阶效应时，它们包括父母的主要影响。现有方法主要依赖于特殊的惩罚功能或算法来在可变选择中执行强大的遗传。我们提出了一种新型的分层标准化程序，以在可变选择中保持强烈的遗传。我们的方法毫不费力地实施，并且适用于任何类型的回归方法的任何变量选择方法。分层标准化的性能与常规标准化相当。我们还提供鲁棒性检查和实际数据分析，以说明我们方法的优点。
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.
