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报告主题:Risk Factor Selection in Rate-making: EM-Adaptive LASSO for Zero-Inflated Poisson Regression Models
报 告 人:朱仲义 教授(复旦大学统计系)
报告时间:2013年6月14日下午2:30-3:45
报告地点:理学院大会议室(学14-514)
报告内容提纲:Risk factor selection is very important in insurance industry, which helps precise rate-making and studying the features of high quality insureds. Zero-inflated data are common in insurance, such as the claim frequency data, and zero-inflation makes the selection of risk factors quite difficult. In this paper, we propose a new risk factor selection approach, EM-Adaptive LASSO, for Zero-Inflated-Poisson(ZIP) regression model, which combines the EM algorithm and adaptive LASSO penalty. Under some regularity conditions, we show that, with probability approaching one, important factors are selected and the redundant factors are excluded. We investigate the finite sample performance of the proposed method through a simulation study and the analysis of a car insurance data, from SAS Enterprise Miner database.
报告人简介:朱仲义,复旦大学统计系教授,博士研究生导师;中国概率统计学会副理事长,国际著名杂志“Statistic Sinica”的Associate Editor;“应用概率统计”,“数理统计与管理”杂志编委,中国统计教材编审委员会委员。专业方向为:非参数和半参数回归模型,保险精算,稳健统计方法,风险分析等。参加过多项国家、省自然科学基金及其他省部级科研项目的研究,主持国家自然科学基金四项、国家社会科学基金一项,参与国家自然科学基金重点项目一项。自从1999年至今多次访问香港大学统计与精算学系、五次访问美国著名大学。近几年发表论文80多篇(其中SCI论文三十多篇,包括在国际顶级刊物:J.R.Stat.Soc B, J.A.S.A., Ann. Statist. 和Biometrika上发表6篇) 被SCI论文引用300多次。
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理学院
2013年6月13日