講座題目：On efficient dimension reduction with respect to the interaction between two response variables
主 講 人：浙江大學駱威研究員
講座時間：2023年12月27日（周三）14：30 -15：30
講座地點：6號學院樓402
主辦單位：新葡萄8883官網AMG、浙江省2011“數據科學與大數據分析協同創新中心”
摘要：
In this paper, we propose the novel theory and methodologies for dimension reduction with respect to the interaction between two response variables, which is a new research problem that has wide applications in missing data analysis, causal inference, and graphical models, etc. We formulate the parameters of interest to be the locally and the globally efficient dimension reduction subspaces, and justify the generality of the corresponding low-dimensional assumption. We then construct estimating equations that characterize these parameters, using which we develop a generic family of consistent, model-free, and easily implementable dimension reduction methods called the dual inverse regression methods. We also build the theory regarding the existence of the globally efficient dimension reduction subspace, and provide a handy way to check this in practice. The proposed work differs fundamentally from the literature of sufficient dimension reduction in terms of the research interest, the assumption adopted, the estimation methods, and the corresponding applications, and it potentially creates a new paradigm of dimension reduction research. Its usefulness is illustrated by simulation studies and a real data example at the end.
主講人簡介：
駱威，2014年畢業于美國賓夕法尼亞州立大學，之后任職于美國Baruch College,于2018年加入浙江大學。駱威的研究方向包括充分降維和因果推斷，在Annals of Statistics, Biometrika, JRSSB等統計國際學術期刊上發表了多篇論文，目前主持國家優秀青年科學基金項目。
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