题目:基于广义估计方程的复杂数据分析方法 报告人:秦国友时间:2020年12月11日 9:00-10:00地点:腾讯会议 ID 228 757 574主办单位:统计学院摘要:该报告基于广义估计方程,提出针对异常点、缺失值和测量误差的纵向数据的统计分析方法。讨论了相关估计的...[详细]
报告题目:Testing for conditional independence: a groupwise dimension reduction-based adaptive-to-model approach报告人:朱学虎 副教授报告摘要: In this paper, we propose an adaptive-to-model test for conditional independence through gro...[详细]
报告题目:Model averaging estimation for probability density functions报告人:邹国华 教授报告摘要: Extraction of information from data is critical in the age of data science. Theoretically probability density function provides comprehens...[详细]
报告题目:Deterministic Sampling of Expensive Posteriors Using Kullback-Leibler Divergence报告人:孙法省 教授报告摘要: This paper introduces a new way of discrete approximation a continuous probability distribution F into a set of repres...[详细]
报告题目:Large-Scale Datastreams Surveillance via Pattern-Oriented-Sampling报告人:邹长亮 教授报告摘要: Monitoring large-scale datastreams with limited resources has become increasingly important for real-time detection of abnormal acti...[详细]
报告题目:Wordlength enumerator for fractional factorial designs 报告人:唐煜 教授报告摘要:While the minimum aberration criterion is popular for selecting good designs with qualitative factors under an ANOVA model, the minimum β-abe...[详细]
报告题目:G-optimal Designs for Hierarchical Linear Models: an Equivalence Theorem and a Nature-inspired Meta-heuristic Algorithm报告人:岳荣先 教授报告摘要:Hierarchical linear models are widely used in many research disciplines and es...[详细]
统计学院研究生2020年评奖评优名单公示,请查看附件[详细]