管理学院管理科学系博士郑陈璐与导师朱建平教授撰写的论文“Promote sign consistency in cure rate model with Weibull lifetime”在SCI期刊AIMS Mathematics（JCR二区）线上刊出。
In survival analysis, the cure rate model is widely adopted when a proportion of subjects have long-term survivors. The cure rate model is composed of two parts: the first part is the incident part which describes the probability of cure (infinity survival), and the second part is the latency part which describes the conditional survival of the uncured subjects (finite survival). In the standard cure rate model, there are no constraints on the relations between the coefficients in the two model parts. However, in practical applications, the two model parts are quite related. It is desirable that there may be some relations between the two sets of the coefficients corresponding to the same covariates. Existing works have considered incorporating a joint distribution or structural effect, which is too restrictive. In this paper, we consider a more flexible model that allows the two sets of covariates can be in different distributions and magnitudes. In many practical cases, it is hard to interpret the results when the two sets of the coefficients of the same covariates have conflicting signs. Therefore, we proposed a sign consistency cure rate model with a sign-based penalty to improve interpretability. To accommodate high-dimensional data, we adopt a group lasso penalty for variable selection. Simulations and a real data analysis demonstrate that the proposed method has competitive performance compared with alternative methods.
郑陈璐，2017级麻花星空mv管理科学系博士，导师朱建平教授，主要研究方向为数据挖掘、大数据风控、信贷风险管理。郑陈璐博士已以第一作者/通讯作者发表SCI、SSCI、CSSCI一类核心期刊论文4篇。&苍产蝉辫;&苍产蝉辫;
（郑陈璐撰稿）
