ArticleJournal of the American Statistical Association2019
A Generic Sure Independence Screening Procedure.
Article in Journal of the American Statistical Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A benchmarking study of feature screening approaches across type 1 diabetes omics studies classification settings.PLoS computational biology · 2026Article
- Global Group Testing and Screening With Dynamic Effects.Statistica Sinica · 2026Article
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- A multi-omics framework for survival mediation analysis of high-dimensional proteogenomic data.PLoS computational biology · 2026Article
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- Detection of LUAD-Associated Genes Using Wasserstein Distance in Multiomics Feature Selection.Bioengineering (Basel, Switzerland) · 2025Article
- Uncertainty Quantification in Epigenetic Clocks via Conformalized Quantile Regression.Genetic epidemiology · 2025Article
- Uncertainty quantification in epigenetic clocks via conformalized quantile regression.medRxiv : the preprint server for health sciences · 2025Article
- Conditional Variable Screening for Ultra-High Dimensional Longitudinal Data With Time Interactions.Biometrical journal. Biometrische Zeitschrift · 2024Article
- RANK-BASED INDICES FOR TESTING INDEPENDENCE BETWEEN TWO HIGH-DIMENSIONAL VECTORS.Annals of statistics · 2024Article
- EFFICIENT ESTIMATION OF THE MAXIMAL ASSOCIATION BETWEEN MULTIPLE PREDICTORS AND A SURVIVAL OUTCOME.Annals of statistics · 2023Article
- Feature Screening for Interval-Valued Response with Application to Study Association between Posted Salary and Required Skills.Journal of the American Statistical Association · 2023Article
- The Kendall interaction filter for variable interaction screening in high dimensional classification problems.Journal of applied statistics · 2023Article
- Conditional screening for ultrahigh-dimensional survival data in case-cohort studies.Lifetime data analysis · 2021Article
- TF-RBP-AS Triplet Analysis Reveals the Mechanisms of Aberrant Alternative Splicing Events in Kidney Cancer: Implications for Their Possible Clinical Use as Prognostic and Therapeutic Biomarkers.International journal of molecular sciences · 2021Article
- Feature screening for case-cohort studies with failure time outcome.Scandinavian journal of statistics, theory and applications · 2021Article
- Weighted Mean Squared Deviation Feature Screening for Binary Features.Entropy (Basel, Switzerland) · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
Extracting important features from ultra-high dimensional data is one of the primary tasks in statistical learning, information theory, precision medicine and biological discovery. Many of the sure independent screening methods developed to meet these needs are suitable for special models under some assumptions. With the availability of more data types and possible models, a model-free generic screening procedure with fewer and less restrictive assumptions is desirable. In this paper, we propose a generic nonparametric sure independence screening procedure, called BCor-SIS, on the basis of a recently developed universal dependence measure: Ball correlation. We show that the proposed procedure has strong screening consistency even when the dimensionality is an exponential order of the sample size without imposing sub-exponential moment assumptions on the data. We investigate the flexibility of this procedure by considering three commonly encountered challenging settings in biological discovery or precision medicine: iterative BCor-SIS, interaction pursuit, and survival outcomes. We use simulation studies and real data analyses to illustrate the versatility and practicability of our BCor-SIS method.
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