Feature screening via false discovery rate control for linear model with multivariate responses
Authors:
- 23 January 2025
- journal article
- research article
- Published by Springer Nature in Statistical Papers
- Vol. 66 (2) , 1-29
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (12031016, 11971324, 11471223)
- the Major Research Projects at Beijing Polytechnic (2024X009-KXD)
- the Interdisciplinary Construction of Bioinformatics and Statistics, Capital Normal University
- the Academy for Multidisciplinary Studies, Capital Normal University
This publication has 35 references indexed in Scilit:
- False Discovery Rate Control via Data SplittingJournal of the American Statistical Association, 2022
- Feature Screening with Latent ResponsesBiometrics, 2022
- False Discovery Rate Control Under General Dependence By Symmetrized Data AggregationJournal of the American Statistical Association, 2021
- Cauchy Combination Test: A Powerful Test With Analytic p-Value Calculation Under Arbitrary Dependency StructuresJournal of the American Statistical Association, 2019
- Projection tests for high-dimensional spiked covariance matricesJournal of Multivariate Analysis, 2019
- Model-Free Feature Screening for Ultrahigh Dimensional Discriminant AnalysisJournal of the American Statistical Association, 2015
- A functional genomic perspective on human well-beingProceedings of the National Academy of Sciences, 2013
- Incorporating group correlations in genome-wide association studies using smoothed group LassoBiostatistics, 2012
- Feature Screening via Distance Correlation LearningJournal of the American Statistical Association, 2012
- Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified ApproachJournal of the Royal Statistical Society Series B: Statistical Methodology, 2003