...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of the American statistical association >Category-Adaptive Variable Screening for Ultra-High Dimensional Heterogeneous Categorical Data
【24h】

Category-Adaptive Variable Screening for Ultra-High Dimensional Heterogeneous Categorical Data

机译：用于超高维异构分类数据的类别 - 自适应变量筛选

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Abstract The populations of interest in modern studies are very often heterogeneous. The population heterogeneity, the qualitative nature of the outcome variable and the high dimensionality of the predictors pose significant challenge in statistical analysis. In this article, we introduce a category-adaptive screening procedure with high-dimensional heterogeneous data, which is to detect category-specific important covariates. The proposal is a model-free approach without any specification of a regression model and an adaptive procedure in the sense that the set of active variables is allowed to vary across different categories, thus making it more flexible to accommodate heterogeneity. For response-selective sampling data, another main discovery of this article is that the proposed method works directly without any modification. Under mild regularity conditions, the newly procedure is shown to possess the sure screening and ranking consistency properties. Simulation studies contain supportive evidence that the proposed method performs well under various settings and it is effective to extract category-specific information. Applications are illustrated with two real datasets. Supplementary materials for this article are available online.
机译：摘要在现代研究中兴趣的人群经常是异质的。人口异质性，结果变量的定性性质和预测因子的高维度在统计分析中提出了重大挑战。在本文中，我们介绍了一种具有高维异构数据的类别自适应筛选程序，即检测特定的类别重要协变量。该提议是一种无模型方法，没有任何对回归模型的规范和自适应过程，即允许该组有源变量在不同类别上变化，从而使其更加灵活地容纳异质性。对于响应选择性采样数据，本文的另一个主要发现是该方法直接工作而不进行任何修改。在温和的规律性条件下，显示新程序具有确保筛选和排名一致性。仿真研究包含支持的证据表明，所提出的方法在各种设置下表现良好，并有效提取特定于类别的信息。应用程序被两个实时数据集说明。本文的补充材料在线提供。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号