Cover Image

Testing composite null hypotheses with high-dimensional dependent data: a computationally scalable FDR-controlling procedure

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lyu, Pengfei, Zhang, Xianyang, Cao, Hongyuan
Format:	Preprint
Published:	2024
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive procedures for boundary FDR control
by: Mostow, Sarah, et al.
Published: (2026)

A novel finite-sample testing procedure for composite null hypotheses via pointwise rejection
by: Park, Joonha, et al.
Published: (2026)

Anytime-valid FDR control with the stopped e-BH procedure
by: Wang, Hongjian, et al.
Published: (2025)

Leveraging the group structure of hypotheses for more powerful multiple testing with FDR control for the filtered rejection set
by: Bogomolov, Marina, et al.
Published: (2025)

A robust and powerful method for assessing replicability of high dimensional data
by: Lei, Haochen, et al.
Published: (2023)

Bringing closure to FDR control: beating the e-Benjamini-Hochberg procedure
by: Xu, Ziyu, et al.
Published: (2025)

FDR controlling procedures with dimension reduction and their application to GWAS with linkage disequilibrium score
by: Jung, Dayeon, et al.
Published: (2025)

Multiple testing of interval composite null hypotheses using randomized p-values
by: Ochieng, Daniel
Published: (2024)

Online FDR Controlling procedures for statistical SIS Model and its application to COVID19 data
by: Hwang, Seohwa, et al.
Published: (2026)

Online multi-layer FDR control
by: Wang, Runqiu, et al.
Published: (2025)

Trade-off between predictive performance and FDR control for high-dimensional Gaussian model selection
by: Lacroix, Perrine, et al.
Published: (2023)

Regression analysis of multiplicative hazards model with time-dependent coefficient for sparse longitudinal covariates
by: Sun, Zhuowei, et al.
Published: (2023)

Statistical Validation of Computer Models: Global and Subdomain Hypothesis Testing
by: Li, Chaoan, et al.
Published: (2026)

Powerful Spatial Multiple Testing via Borrowing Neighboring Information
by: Deng, Linsui, et al.
Published: (2022)

A General Framework for Multiple Testing via E-value Aggregation and Data-Dependent Weighting
by: Li, Guanxun, et al.
Published: (2023)

Sequential FDR and pFDR control under arbitrary dependence, with application to pharmacovigilance database monitoring
by: Hankin, Michael, et al.
Published: (2024)

Synthetic-Powered Multiple Testing with FDR Control
by: Lee, Yonghoon, et al.
Published: (2026)

A scalable Bayesian functional factor model for high-dimensional longitudinal molecular data
by: Jaoua, Salima, et al.
Published: (2026)

A general approach to construct powerful tests for intersections of one-sided null-hypotheses based on influence functions
by: Pipper, Christian Bressen, et al.
Published: (2025)

Subsampling-based Tests in Mediation Analysis
by: Roy, Asmita, et al.
Published: (2024)

Improving online FDR procedures via online analogs of e-closure and compound e-values
by: Xu, Ziyu, et al.
Published: (2026)

Nonparametric Block Bootstrap Kolmogorov-Smirnov Goodness-of-Fit Test
by: Chandy, Mathew, et al.
Published: (2025)

A powerful procedure that controls the false discovery rate with directional information
by: Tian, Zhaoyang, et al.
Published: (2025)

Conformal novelty detection for replicate point patterns with FDR or FWER control
by: Biscio, Christophe A. N., et al.
Published: (2025)

Powerful Large-scale Inference in High Dimensional Mediation Analysis
by: Roy, Asmita, et al.
Published: (2024)

Testing common structure in high-dimensional factor models: change-point and two-sample procedures
by: Düker, Marie-Christine, et al.
Published: (2024)

fastcpd: Fast Change Point Detection in R
by: Li, Xingchi, et al.
Published: (2024)

A generalized e-value feature detection method with FDR control at multiple resolutions
by: Yu, Chengyao, et al.
Published: (2024)

Doubly robust and computationally efficient high-dimensional variable selection
by: Chakraborty, Abhinav, et al.
Published: (2024)

Simultaneous testing of hypotheses and alternatives
by: Koldanov, P. A., et al.
Published: (2025)

Generalized Boundary FDR Control under Arbitrary Dependence: An Approach on Closure Principle
by: Zhang, Yifan, et al.
Published: (2026)

Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing
by: Yan, Jian, et al.
Published: (2022)

A covariate-dependent Cholesky decomposition for high-dimensional covariance regression
by: Kim, Rakheon, et al.
Published: (2026)

Comparison study of variable selection procedures in high-dimensional Gaussian linear regression
by: Lacroix, Perrine, et al.
Published: (2021)

Familial inference: tests for hypotheses on a family of centres
by: Thompson, Ryan, et al.
Published: (2022)

On the existence of powerful p-values and e-values for composite hypotheses
by: Zhang, Zhenyuan, et al.
Published: (2023)

A General Framework for Powerful Confounder Adjustment in Omics Association Studies
by: Roy, Asmita, et al.
Published: (2022)

Testing independence in the presence of missing data: high-dimensional case
by: Cuparić, Marija, et al.
Published: (2026)

Spatial scale-aware tail dependence modeling for high-dimensional spatial extremes
by: Shi, Muyang, et al.
Published: (2024)

SCORE: A Unified Framework for Overshoot Refund in Online FDR Control
by: Kuang, Qi, et al.
Published: (2026)