research
∙
04/21/2023
Joint Mirror Procedure: Controlling False Discovery Rate for Identifying Simultaneous Signals
In many applications, identifying a single feature of interest requires ...
share
research
∙
04/13/2023
Adaptive Testing for Alphas in High-dimensional Factor Pricing Models
This paper proposes a new procedure to validate the multi-factor pricing...
research
∙
01/10/2023
High Dimensional Analysis of Variance in Multivariate Linear Regression
In this paper, we develop a systematic theory for high dimensional analy...
research
∙
10/31/2022
Powerful Spatial Multiple Testing via Borrowing Neighboring Information
Clustered effects are often encountered in multiple hypothesis testing o...
research
∙
10/21/2022
Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis
One common approach to detecting change-points is minimizing a cost func...
research
∙
10/15/2022
A nonparametric two-sample conditional distribution test
Testing the equality of two conditional distributions is at the core of ...
research
∙
06/02/2022
Likelihood-based Changepoint Detection in Preferential Attachment Networks
Generative, temporal network models play an important role in analyzing ...
research
∙
05/23/2022
A General Framework for Powerful Confounder Adjustment in Omics Association Studies
Genomic data are subject to various sources of confounding, such as batc...
research
∙
04/03/2022
A Modern Theory for High-dimensional Cox Regression Models
The proportional hazards model has been extensively used in many fields ...
research
∙
12/31/2021
Kernel Two-Sample Tests in High Dimension: Interplay Between Moment Discrepancy and Dimension-and-Sample Orders
Motivated by the increasing use of kernel-based metrics for high-dimensi...
research
∙
05/19/2021
High-dimensional Change-point Detection Using Generalized Homogeneity Metrics
Change-point detection has been a classical problem in statistics and ec...
research
∙
04/01/2021
LinDA: Linear Models for Differential Abundance Analysis of Microbiome Compositional Data
One fundamental statistical task in microbiome data analysis is differen...
research
∙
03/29/2021
Optimal False Discovery Rate Control for Large Scale Multiple Testing with Auxiliary Information
Large-scale multiple testing is a fundamental problem in high dimensiona...
research
∙
01/10/2021
Kernel-Distance-Based Covariate Balancing
A common concern in observational studies focuses on properly evaluating...
research
∙
11/02/2020
Covariate Adaptive Family-wise Error Rate Control for Genome-Wide Association Studies
The family-wise error rate (FWER) has been widely used in genome-wide as...
research
∙
06/03/2020
Structure Adaptive Lasso
Lasso is of fundamental importance in high-dimensional statistics and ha...
research
∙
09/30/2019
A New Framework for Distance and Kernel-based Metrics in High Dimensions
The paper presents new metrics to quantify and test for (i) the equality...
research
∙
09/11/2019
Covariate Adaptive False Discovery Rate Control with Applications to Omics-Wide Multiple Testing
Conventional multiple testing procedures often assume hypotheses for dif...
research
∙
02/08/2019
Distance-based and RKHS-based Dependence Metrics in High Dimension
In this paper, we study distance covariance, Hilbert-Schmidt covariance ...
research
∙
11/01/2018
High Dimensional Robust Inference for Cox Regression Models
We consider high-dimensional inference for potentially misspecified Cox ...
research
∙
11/25/2017
