Sufficient variable selection using independence measures for continuous response
Sufficient variable selection using independence measures for continuous response
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DOI：
10.1016/j.jmva.2019.04.006
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发表时间：
2019-09
期刊：
影响因子：
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通讯作者：
Baoying Yang;Xiangrong Yin;N. Zhang
中科院分区：
文献类型：
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作者：
Baoying Yang;Xiangrong Yin;N. Zhang
我们提出了两种充分的变量选择方法，即对连续响应使用独立性度量的一阶段和两阶段方法，以距离相关和Hilbert-Schmidt独立准则相关为例。通过仿真和实际数据分析，证明了该方法相对于现有的一些边缘筛选方法的优越性。我们的过程是无模型的，因此对模型错误规范具有健壮性。当一些活跃的预测者与反应略微无关时，它们特别有用。
We propose two sufficient variable selection procedures, i.e., one- and two-stage approaches using independence measures for continuous response, illustrated by distance correlation and the Hilbert–Schmidt Independence Criterion correlation. We show the advantages of the proposed procedures over some existing marginal screening methods through simulations and a real data analysis. Our procedures are model-free and thus robust against model mis-specification. They are particularly useful when some active predictors are marginally independent of the response.