6 papers
Revisiting dependence in multiple testing: empirical distribution approaches for FDP control
Fangyong Zheng, Pengfei Li, Yuan Jiang +1
Large-scale multiple hypothesis testing is central to the analysis of high-throughput data, where controlling false discoveries is critical. Classical procedures typically rely on…
Asymptotic Uncertainty of False Discovery Proportion for Dependent -Tests
Meng Mei, Yuan Jiang
Multiple testing is a fundamental problem in high-dimensional statistical inference. Although many methods have been proposed to control false discoveries, it is still a challengin…
Compositional Graphical Lasso Resolves the Impact of Parasitic Infection on Gut Microbial Interaction Networks in a Zebrafish Model
Chuan Tian, Duo Jiang, Austin Hammer +2
Understanding how microbes interact with each other is key to revealing the underlying role that microorganisms play in the host or environment and to identifying microorganisms as…
Reference-Invariant Inverse Covariance Estimation with Application to Microbial Network Recovery
Chuan Tian, Duo Jiang, Yuan Jiang
The interactions between microbial taxa in microbiome data has been under great research interest in the science community. In particular, several methods such as SPIEC-EASI, gCoda…
Asymptotic Uncertainty of False Discovery Proportion
Meng Mei, Tao Yu, Yuan Jiang
Multiple testing has been a popular topic in statistical research. Although vast works have been done, controlling the false discoveries remains a challenging task when the corresp…
Stability Approach to Regularization Selection for Reduced-Rank Regression
Canhong Wen, Qin Wang, Yuan Jiang
The reduced-rank regression model is a popular model to deal with multivariate response and multiple predictors, and is widely used in biology, chemometrics, econometrics, engineer…