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刘玉坤教授学术报告预告

信息来源: 发布日期: 2016-12-22浏览次数:

刘玉坤教授学术报告预告

报告题目:Maximum empirical likelihood estimation for abundance in a closed population from capture-recapture datas

报告人:刘玉坤

主办单位:统计学院

时间:1230日下午16:00-17:00

地点:科技楼二楼北会议室

AbstractCapture-recapture experiments are widely used to collect the capture-recapture data needed to estimate the abundance of a closed population. To account for the observable heterogeneity in the capture probabilities, Alho (1990) proposed a semiparametric model in which the capture probabilities are modelled by a parametric model and the distribution of individual characteristics is left unspecied. A conditional likelihood method was then proposed to obtain point estimates and Wald-type condence intervals for the abundance. Empirical studies show that the small-sample distribution of the maximum conditional likelihood estimator is strongly skewed to the right, which may produce Wald-type condence intervals with lower limits that are less than the number of captured individuals or even negative. In this paper, we propose a full empirical likelihood approach based on Alho (1990)'s model. We show that the empirical likelihood ratio for the abundance is asymptotically chi-square with one degree of freedom. Simulation studies show that the empirical-likelihood-based method is superior to the conditional-likelihood-based method: the empirical likelihood ratio based condence interval has much better coverage, and the maximum empirical likelihood estimator has a smaller mean square error. We analyze three real data sets to illustrate the advantages of the proposed empirical likelihood method.

刘玉坤简介:华东师范大学金融与统计学院副教授、博士生导师,研究领域包括经验似然方法及其应用、小区域估计、生存分析、非参数和半参数回归。20096月在南开大学统计学系获得博士学位。200711月到200810月作为联合培养博士研究生访问加拿大英属哥伦比亚大学统计系。发表学术论文20余篇,其中在统计学顶级期刊The Annals of Statistics 发表论文两篇。