A semiparametric model for observational data combines a parametric form for some
component of the data generating process (usually the behavioral relation between the …

Quantile regression (QR) has received increasing attention in recent years and applied to
wide areas such as investment, finance, economics, medicine and engineering. Compared …

Quantile regression is gradually emerging as a unified statistical methodology for estimating
models of conditional quantile functions. By complementing the exclusive focus of classical …

Survival analysis arises in many fields of study including medicine, biology, engineering,
public health, epidemiology, and economics. This book provides a comprehensive treatment …

Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen
used them in the 60s and 70s in describing populations. Since then, the authors of many …

This volume examines modern techniques and research problems in the analysis of lifetime
data analysis. This area of statistics deals with time-to-event data which is complicated not …

Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data
Page 1 The Annals of Statistics 2013, Vol. 41, No. 1, 342–369 DOI: 10.1214/13-AOS1087 © …

We argue, that due to the curse of dimensionality, there are major difficulties with any pure or
smoothed likelihood‐based method of inference in designed studies with randomly missing …

Using quantile regression to analyze survival times offers an valuable complement to
traditional Cox proportional hazards modelling. Unfortunately, this approach has been …

Quantile regression offers great flexibility in assessing covariate effects on event times,
thereby attracting considerable interests in its applications in survival analysis. But currently …