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]
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]
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]
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]
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]
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]
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]
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]