• 统计机器学习与因果效应评估系列学术报告(10) 英国爱丁堡大学陈泽汛博士报告 2024-08-28

    报告题目:Generic Inference for Gaussian Process Models报告人: 陈泽汛 博士 (英国爱丁堡大学)报告时间:2024年8月30日下午 15:00-16:00报告地点:腾讯会议(215-121-098)报告摘要:Gaussian Process (GP) modelling is pivotal in machine learnin...[详细]

  • 北京理工大学助理教授虞俊学术报告 2024-08-23

    Title: Subsampling techniques: Method, Design, and ApplicationsAbstract: Survey sampling is one of the most practiced areas of statistics. This lecture will center on the understanding of some basic survey sampling methods in analysis bi...[详细]

  • 华东师范大学统计学院王亚平教授学术报告 2024-08-23

     Title: Uniform designs of experiments with mixtures under the criterion mean L1-distance and a new approach to Scheffé-type designs Abstract: Mixture experiments analyze how changes in component proportions impact the response variab...[详细]

  • 天津大学荣喜民教授学术报告 2024-06-24

    报告题目:Target benefit pension plan with longevity risk and intergenerational equity报告摘要:  We study a stochastic model for a target benefit pension plan suffering from rising longevity and falling fertility. Policies for postponin...[详细]

  • 天津大学赵慧教授学术报告 2024-06-24

    报告题目:Optimal investment strategies and intergenerational risk sharing for target benefit pension plans under habit formation报告摘要:This paper investigates a stochastic model of a continuous-time target benefit pension system with...[详细]

  • 英国曼彻斯特大学韩杨副教授学术报告 2024-06-18

    Title: Exact simultaneous confidence intervals for logical selection of a biomarker cut-point Abstract: Four new principles are proposed in this work for logical biomarker cut-point selection methods to adhere to: subgroup sensibility, s...[详细]

  • 大连理工大学王晓光副教授学术报告 2024-06-18

      Title: Efficient auxiliary information synthesis for cure rate model  Abstract: We propose a new auxiliary information synthesis method to utilize subgroup survival information at multiple time points under the semi-parametric mixture ...[详细]

  • 美国北卡大学夏洛特分校蒋建成教授学术报告 2024-06-11

    报告题目:Inference for possibly misspecified generalized linear models with non-polynomial dimensional nuisance parameters报告摘要:It is a routine practice in statistical modelling to first select variables and then make inference for ...[详细]

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