When I was a graduate student more than twenty five years ago, I was struggling to read
many statistical research papers. This is particularly true at the time when I had passed my …

The populations of interest in modern studies are very often heterogeneous. The population
heterogeneity, the qualitative nature of the outcome variable and the high dimensionality of …

The aim of this paper is to develop a weighted functional linear Cox regression model that
accounts for the association between a failure time and a set of functional and scalar …

We consider the problem of estimating the nonparametric function in nonparametric logistic
regression under semi‐supervised framework, where a relatively small size labeled data set …

A novel model‐free interaction screening approach called the hybrid metrics is introduced
for high‐dimensional heterogeneous data analysis. The metrics established based on the …

Confidence sets are of key importance in high-dimensional statistical inference. Under case–
control study, a popular response-selective sampling design in medical study or …

Imbalanced data, in which the data exhibit an unequal or highly-skewed distribution
between its classes/categories, are pervasive in many scientific fields, with application range …

Functional regression is a cornerstone for understanding complex relationships where
predictors or responses (or both) are functions. A particularly powerful framework within this …

Using conditional characteristic function as a screening index, a new model-free screening
procedure is proposed to deal with variable screening problems in large-scale high …

Any data set exhibiting an unequal or highly-skewed distribution between its
classes/categories can be regarded as imbalanced data. Due to privacy concern and other …