7 citations · 21 across the 11 of their papers we have counts for
12 papers
Kernel Cox partially linear regression: building predictive models for cancer patients' survival
Yaohua Rong, Sihai Dave Zhao, Xia Zheng +1
Wide heterogeneity exists in cancer patients' survival, ranging from a few months to several decades. To accurately predict clinical outcomes, it is vital to build an accurate pred…
Nonparametric empirical Bayes biomarker imputation and estimation
Alton Barbehenn, Sihai Dave Zhao
Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from det…
A nonparametric regression alternative to empirical Bayes approaches to simultaneous estimation
Alton Barbehenn, Sihai Dave Zhao
The simultaneous estimation of multiple unknown parameters lies at heart of a broad class of important problems across science and technology. Currently, the state-of-the-art perfo…
Linear shrinkage for predicting responses in large-scale multivariate linear regression
Yihe Wang, Sihai Dave Zhao
We propose a new prediction method for multivariate linear regression problems where the number of features is less than the sample size but the number of outcomes is extremely lar…
Capturing patterns of variation unique to a specific dataset
Robin Tu, Alexander H. Foss, Sihai D. Zhao
Capturing patterns of variation present in a dataset is important in exploratory data analysis and unsupervised learning. Contrastive dimension reduction methods, such as contrasti…
A Compound Decision Approach to Covariance Matrix Estimation
Huiqin Xin, Sihai Dave Zhao
Covariance matrix estimation is a fundamental statistical task in many applications, but the sample covariance matrix is sub-optimal when the sample size is comparable to or less t…
Estimation and inference for the indirect effect in high-dimensional linear mediation models
Ruixuan Rachel Zhou, Liewei Wang, Sihai Dave Zhao
Mediation analysis is difficult when the number of potential mediators is larger than the sample size. In this paper we propose new inference procedures for the indirect effect in…
Simultaneous estimation of normal means with side information
Sihai Dave Zhao
The integrative analysis of multiple datasets is an important strategy in data analysis. It is increasingly popular in genomics, which enjoys a wealth of publicly available dataset…
Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure
Tao Yang, Paul Thompson, Sihai Zhao +1
Genome-wide association studies (GWA studies or GWAS) investigate the relationships between genetic variants such as single-nucleotide polymorphisms (SNPs) and individual traits. R…
Optimal detection of weak positive latent dependence between two sequences of multiple tests
Sihai Dave Zhao, T. Tony Cai, Hongzhe Li
It is frequently of interest to jointly analyze two paired sequences of multiple tests. This paper studies the problem of detecting whether there are more pairs of tests that are s…
Nonparametric empirical Bayes and maximum likelihood estimation for high-dimensional data analysis
Lee H. Dicker, Sihai D. Zhao
Nonparametric empirical Bayes methods provide a flexible and attractive approach to high-dimensional data analysis. One particularly elegant empirical Bayes methodology, involving…
Sure screening for estimating equations in ultra-high dimensions
Sihai D. Zhao, Yi Li
As the number of possible predictors generated by high-throughput experiments continues to increase, methods are needed to quickly screen out unimportant covariates. Model-based sc…