High-dimensional case-control analysis is encountered in many different settings in
genomics. In order to rank genes accordingly, many different scores have been proposed …

The improvement of long‐term transplant organ and patient survival remains a critical
challenge following kidney transplantation. Proteomics and biochemical profiling …

This article introduces covariance regression analysis for ap-dimensional response vector.
The proposed method explores the regression relationship between the p-dimensional …

Background DNA microarrays provide data for genome wide patterns of expression between
observation classes. Microarray studies often have small samples sizes, however, due to …

Estimation of variances and covariances is required for many statistical methods such as t‐
test, principal component analysis and linear discriminant analysis. High‐dimensional data …

This article addresses a common type of data encountered in genomic studies, where a
signal along a linear chromosome exhibits a hierarchical organization. We propose a novel …

High-dimensional data such as microarrays have brought us new statistical challenges. For
example, using a large number of genes to classify samples based on a small number of …

High-throughput expression profiling techniques bring novel tools and also statistical
challenges to genetic research. In addition to detecting differentially expressed genes …

We consider the problem of empirical Bayes estimation of multiple variances when provided
with sample variances. Assuming an arbitrary prior on the variances, we derive different …

We construct empirical Bayes intervals for a large number p of means. The existing intervals
in the literature assume that variances σ i 2 are either equal or unequal but known. When the …