260 citations · 438 across the 13 of their papers we have counts for
13 papers
Controlling the false discovery rate in high-dimensional linear models using model-X knockoffs and -values
Jinyuan Chang, Chenlong Li, Cheng Yong Tang +1
We propose a novel multiple testing methodology for controlling the false discovery rate (FDR) in high-dimensional linear models that integrates model-X knockoff techniques with de…
Applied Regression Analysis of Correlations for Correlated Data
Jie Hu, Yu Chen, Chenlei Leng +1
Correlated data are ubiquitous in today's data-driven society. While regression models for analyzing means and variances of responses of interest are relatively well-developed, the…
Pre-processing with Orthogonal Decompositions for High-dimensional Explanatory Variables
Xu Han, Ethan X Fang, Cheng Yong Tang
Strong correlations between explanatory variables are problematic for high-dimensional regularized regression methods. Due to the violation of the Irrepresentable Condition, the po…
Adjusting the Benjamini-Hochberg method for controlling the false discovery rate in knockoff assisted variable selection
Sanat K. Sarkar, Cheng Yong Tang
The knockoff-based multiple testing setup of Barber & Candes (2015) for variable selection in multiple regression where sample size is as large as the number of explanatory variabl…
Missing at Random or Not: A Semiparametric Testing Approach
Rui Duan, C. Jason Liang, Pamela Shaw +2
Practical problems with missing data are common, and statistical methods have been developed concerning the validity and/or efficiency of statistical procedures. On a central focus…
High-dimensional Interactions Detection with Sparse Principal Hessian Matrix
Cheng Yong Tang, Ethan X. Fang, Yuexiao Dong
In statistical learning framework with regressions, interactions are the contributions to the response variable from the products of the explanatory variables. In high-dimensional…