题目：Bayesian semiparametric quantile regression modeling for estimating earthquake fatality risk
主讲：李云仙
时间：2017年12月8日 10:00-11:00
地点：明德主楼 1030会议室
简介：
李云仙，毕业于香港中文大学统计系，现为云南财经大学副教授，硕导，保险系主任。研究方向为：贝叶斯统计，非寿险精算。
Yunxian Li joined Yunnan University of Finance and Economics in July 2010. She completed her PhD degree at the Chinese University of Hong Kong in 2010. From Sep. 2013, she has been an associate professor in Finance at Yunnan University of Finance and Economics. Her current research focuses on Bayesian statistics and non-life actuarial science, and catastrophic risk management.
摘要：
Earthquake often results in significant life and property losses. Due to its limitation in analyzing catastrophic loss, mean regression may not be appropriate for analyzing fatality risk caused by earthquake. We developed a Bayesian semiparametric quantile regression model for count data. The count responses are converted to continuous responses through the “jittered” method and a transform function. A Bayesian semiparametric quantile regression modeling approach is then developed. The error distribution in the quantile regression model is assumed to be a mixture of asymmetric Laplace distributions constructed with Dirichlet process. Historical death tolls of China caused by earthquakes from 1969 to 2006 are used for fitting and a parametric model is employed for model comparison. The results of model comparison show that the proposed semiparametric quantile regression model outperforms the parametric model. The empirical analysis illustrates that the impact of earthquake magnitude on death tolls is significant. Moreover, the impact of the magnitude is more pronounced on higher percentiles of death tolls.