報告題目：Quantile correlation-based variable selection
報 告 人：唐年勝 教授 雲南大學
報告時間：2021年7月1日 16:00-17:00
報告地點：騰訊會議 ID：697 814 152 會議密碼：0701
校内聯系人：朱複康 fzhu@jlu.edu.cn
報告摘要：This paper is concerned with identifying important features in high dimensional data analysis, especially when there are complex relationships among predictors. Without any specification of an actual model, we first introduce a multiple testing procedure based on the quantile correlation to select important predictors in high dimensionality. The quantile-correlation statistic is able to capture a wide range of dependence. A stepwise procedure is studied for further identifying important variables. Moreover, a sure independent screening based on the quantile correlation is developed in handling ultrahigh dimensional data. It is computationally efficient and easy to implement. We establish the theoretical properties under mild conditions. Numerical studies including simulation studies and real data analysis contain supporting evidence that the proposal performs reasonably well in practical settings.
報告人簡介：唐年勝，雲南大學二級教授、數學與統計學院院長、博士生導師。國家傑出青年科學基金獲得者，入選教育部“新世紀優秀人才”計劃、國家百千萬人才工程，獲得“國家有突出貢獻中青年專家”榮譽稱号，享受國務院政府特殊津貼；雲南省科技領軍人才、首批“雲嶺學者”和“省委聯系專家”、中青年學術和技術帶頭人、雲南省高等學校教學名師，雲南省高校“統計與信息技術重點實驗室”負責人，“雲南大學複雜數據統計推斷方法研究”省創新團隊帶頭人；國際統計學會推選會員（Elected ISI Member），國際泛華統計學會理事會成員（Board of Directors）；2018年獲ICSA傑出服務獎。主要從事統計診斷、非線性模型、生物醫學統計等方面的研究，在國内外學術刊物發表論文150餘篇，其中SCI檢索120餘篇；獲得省部級科研獎勵9項。
