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學(xué)術(shù)報(bào)告:A Unified Approach for Bayesian Envelope Models

  報(bào)告題目:A Unified Approach for Bayesian Envelope Models 

  報(bào)告時(shí)間:2019年7月1日(星期一)16:00

  報(bào)告地點(diǎn)北辰校區(qū)理學(xué)院西教五416

  報(bào)告嘉賓:Su Zhihua

 

  報(bào)告概要:The envelope model is a nascent construct that aims to increase efficiency in multivariate analysis. It has been used in many contexts including linear regression, generalized linear models, matrix/tensor variate regression, reduced rank regression, and quantile regression, and has showed the potential to provide substantial efficiency gains. Virtually all of these advances, however, have been made from a frequentist perspective, and the literature addressing envelope models from a Bayesian point of view is sparse. The objective of this talk is to propose a Bayesian framework that is applicable across various envelope model contexts. The proposed framework aids straightforward interpretation of model parameters and allows easy incorporation of prior information. We provide a simple block Metropolis-within-Gibbs MCMC sampler for practical implementation of our method.

  

  嘉賓簡介:Su Zhihua, 2006年于復(fù)旦大學(xué)數(shù)學(xué)系獲學(xué)士學(xué)位,2012年于明尼蘇達(dá)大學(xué)統(tǒng)計(jì)系獲博士學(xué)位。現(xiàn)為佛羅里達(dá)大學(xué)統(tǒng)計(jì)系 Associate Professor。主要從事多元分析、數(shù)據(jù)降維、模型選擇等方面的研究工作。已經(jīng)在Annals of Statistics、Biometrika、Journal of the Royal Statistical Society: Series B 等期刊發(fā)表論文近20篇。