In the era of precision medicine, time-to-event outcomes such as time to death or
progression are routinely collected, along with high-throughput covariates. These high …

CoVaR is a measure for systemic risk of the networked financial system conditional on
institutions being under distress. The analysis of systemic risk is the focus of recent …

This study undertook a comprehensive application of 15 data mining (DM) models, most of
which have, thus far, not been commonly used in environmental sciences, to predict land …

Quantile regression has become a valuable tool to analyze heterogeneous covaraite-
response associations that are often encountered in practice. The development of quantile …

Understanding the spatial distribution of soil salinity is required to conserve land against
degradation and desertification. Against this background, this study is the first attempt to …

In this paper, we consider a quantile fused LASSO regression model that combines quantile
regression loss with the fused LASSO penalty. Intuitively, this model offers robustness to …

Censored quantile regression (CQR) has emerged as a useful regression tool for survival
analysis. Some commonly used CQR methods can be characterized by stochastic integral …

Hypothesis tests in models whose dimension far exceeds the sample size can be formulated
much like the classical studentized tests only after the initial bias of estimation is removed …

With the availability of high-dimensional genetic biomarkers, it is of interest to identify
heterogeneous effects of these predictors on patients' survival, along with proper statistical …

Quantile functions are important in characterizing the entire probability distribution of a
random variable, especially when the tail of a skewed distribution is of interest. This article …