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Ultrahigh dimensional feature screening for additive model with multivariate response

机译:多元响应附加模型的超高尺寸特征筛选

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摘要

We consider feature screening for ultrahigh dimensional additive model with multivariate response in this paper. A new method named generalized correlation based projection screening is proposed by using generalized correlation between each predictor and multivariate response. The sure screening and ranking consistency properties are established under some regularized conditions for the proposed procedure. In addition, we construct an iterative version of the proposed screening procedure to enhance the finite sample screening performance. Both simulation studies and the real data analysis demonstrate that the proposed method works effectively.
机译:我们考虑了本文具有多变量响应的超高尺寸添加剂模型的特征筛选。通过使用每个预测器和多变量响应之间的广义相关性提出了一种名为广义相关的投影筛选的新方法。确保筛选和排名一致性属性在提出的程序的某些正则化条件下建立。此外,我们构建了建议的筛选程序的迭代版本,以增强有限的样本筛选性能。仿真研究和实际数据分析都表明该方法有效地工作。

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