報告題目:A New Bayesian Strength of Evidence for Testing a Point Null Hypothesis
報告所屬學科:管理科學與工程
報告人:汪敏(美國德州大學圣安東尼奧分校)
報告時間:2020年11月2日 09:00
報告地點:騰訊會議ID:509708658
報告摘要:
Abstract: The frequentist evidence expressed in terms of the observed level of significance, and the Bayesian evidence expressed through the posterior probability and the Bayes factor, are two main statistical streams of thought for testing a point null hypothesis. However, they may give rise to different decisions in practical situations and could even cast serious doubt on the adequacy of the two schools of evidence for hypothesis testing. In this talk, we propose a new Bayesian strength of evidence, which can not only reconcile the disagreement between frequentists and Bayesians in many classical examples in which Lindley’s paradox occurs,but also is shown to be a Bayes test under some specific loss functions. Thus, it can be viewed as an objective and automatic Bayesian approach to hypothesis testing. Finally, two applications are provided for illustrative purposes.
報告人簡介:
汪敏(Min Wang),美國德州大學圣安東尼奧分校 (University of Texas at San Antonio) 商學院管理科學與統計系副教授(獲終身教職),博士生導師。2010年5月于美國克萊姆森大學(Clemson University)獲得統計碩士學位;2013年5月于克萊姆森大學大學獲得統計博士學位。2013年8月- 2017年12月在美國密歇根理工大學數學科學系工作和在2017年8月破格提前提升為副教授并獲得終身任期教授資格;現在在德州大學圣安東尼奧分校從事教學科研工作。近年來,先后參與和主持了美國自然科學基金委(NSF),密歇根交通部,以及美國衛生院(NIH)的研究課題。在各類同行評議的國際權威期刊上發表了研究文章50余篇。研究方向:貝葉斯統計;計算統計;統計推斷;質量和可靠性工程研究;高維數據分析和統計應用。