Score test variable screening.
Score test variable screening.
复制标题
得分测试变量筛选。
作者：
Zhao SD;Li Y
Variable screening has emerged as a crucial first step in the analysis of high-throughput data, but existing procedures can be computationally cumbersome, difficult to justify theoretically, or inapplicable to certain types of analyses. Motivated by a high-dimensional censored quantile regression problem in multiple myeloma genomics, this paper makes three contributions. First, we establish a score test-based screening framework, which is widely applicable, extremely computationally efficient, and relatively simple to justify. Secondly, we propose a resampling-based procedure for selecting the number of variables to retain after screening according to the principle of reproducibility. Finally, we propose a new iterative score test screening method which is closely related to sparse regression. In simulations we apply our methods to four different regression models and show that they can outperform existing procedures. We also apply score test screening to an analysis of gene expression data from multiple myeloma patients using a censored quantile regression model to identify high-risk genes.
登录
查看更多内容
影响因子：
5.8
作者：
He, Qianchuan;Lin, Dan-Yu
通讯作者：
Lin, Dan-Yu
基于稳健等级相关的筛选
影响因子：
4.5
作者：
Li, Gaorong;Peng, Heng;Zhu, Lixing
通讯作者：
Zhu, Lixing
影响因子：
45.3
作者：
Decaux, Olivier;Lode, Laurence;Minvielle, Stephane
通讯作者：
Minvielle, Stephane
影响因子：
3.7
作者：
Fan J;Feng Y;Song R
通讯作者：
Song R
影响因子：
3.7
作者：
HOEFFDING, W
通讯作者：
HOEFFDING, W