Stochastic Quasi-likelihood for Case-Control Point Pattern Data
时间:2018.06.08 浏览次数:633
主题 Stochastic Quasi-likelihood for Case-Control Point Pattern Data
  • 演讲人 Ganggang Xu
  • 时间 2018年06月13日 星期三 下午3:00-5:00
  • 地点 浙江大学玉泉校区工商管理楼二楼200-9报告厅
  • 主办单位 浙江大学数据科学研究中心、浙江大学统计学研究所

摘要: We propose a novel stochastic quasi-likelihood estimation procedure for case-control point processes. Quasi-likelihood for point processes depends on a certain optimal weight function and for the new method the weight function is stochastic since it depends on the control point pattern. The new procedure also provides a computationally efficient implementation of quasi-likelihood for univariate point processes in which case a synthetic control point process is simulated by the user. Under mild conditions, the proposed approach yields consistent and asymptotically normal parameter estimators. We further show that the estimators are optimal in the sense that the associated Godambe information is maximal within a wide class of estimating functions for case-control point processes.

许刚刚博士简介:Ganggang Xu is currently an assistant professor of Statistics in the Department of Mathematical Sciences at Binghamton University - The State University of New York. He obtained his PhD in Statistics in 2011 from Texas A&M University and a B.S. in Statistics in 2006from Zhejiang University, China.

联系人: 张立新教授