This article develops a nonparametric varying-coefficient approach for modeling the expectile-based value at risk (EVaR). EVaR has an advantage over the conventional quantile-based VaR (QVaR) of being more sensitive to the magnitude of extreme losses. EVaR can also be used for calculating QVaR...

We study estimation and inference in a marginal proportional hazards model that can handle (1) linear effects, (2) non-linear effects and (3) interactions between covariates. The model under consideration is an amalgamation of three existing marginal proportional hazards models studied in the...

We develop composite estimators and its large sample properties for the additive risk model with length-biased and right-censored data. We also conduct simulation studies to confirm the good finite sample performance of our methods and then give a real data example.

In the study of comparing treatment effects, the data structures of two samples may be different. In this paper, we develop a unified semiparametric estimating equation approach to estimate various types of treatment effects with right-censored and length-biased data based on a semiparametric...

In this paper, we consider a flexible class of semiparametric varying-coefficient mean residual lifetime (MRL) models that depended on an exposure variable where some effects may be functions of the exposure variables and some may be constants. We develop three-step estimation procedures to...