題 目：Robust Variable Selection of Joint Frailty Model for Panel Count Data
主 講 人：趙曉兵教授
主 持 人：羅季副教授
時 間：2016年10月11號（周二）14:40-15:40
地 點(diǎn)：數(shù)據(jù)科學(xué)學(xué)院樓（6號學(xué)院樓）415教室
主講人簡介：
趙曉兵教授，獲香港理工大學(xué)哲學(xué)博士學(xué)位,，華東師范大學(xué)博士后?，F(xiàn)為浙江財經(jīng)大學(xué)數(shù)據(jù)科學(xué)學(xué)院教授，浙江省高校中青年學(xué)科帶頭人,。主要研究方向為生存分析,、復(fù)發(fā)事件數(shù)據(jù)分析、高維數(shù)據(jù)分析,，以及保險精算中相關(guān)問題,。在統(tǒng)計學(xué)、保險精算等領(lǐng)域主流期刊Statistica Sinica, Journal of Multivariate Analysis, Statistics in Medicine, Insurance:Mathematics and Economics等期刊發(fā)表論文30余篇,；主持國家自然科學(xué)基金2項,、浙江省自然科學(xué)基金2項；多次到澳大利亞麥考瑞大學(xué),、美國西北大學(xué)進(jìn)行學(xué)術(shù)訪問,。
摘 要： Panel count data arise when the subjects are examined or observed at discrete time points of the event history. Analysis of panel count data has recently received a great deal of attention in the literature. Low-dimensional covariates have been commonly assumed in the existing literature. In practice, however, the panel count data may often involve high-dimensional covariates. The literature on panel count data with high dimensional covariates has so far been quite limited. In this paper, a robust variable selection approach based on the quantile regression function in a joint frailty model is proposed to analyze panel count data with high-dimensional covariates. A three step estimation procedure is developed to select variables and estimate the regression coefficients. The consistency and oracle property are established under some suitable conditions. Simulations are carried out to confirm and assess the performance of the proposed method and an example is demonstrated on a dataset from a bladder tumor study.
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