近日，广州大学经济与统计学院崔霞副院长与Runze Li, Guangren Yang and Wang Zhou合作的学术论文“Empirical likelihood test for a large dimensional mean vector”被统计学四大期刊之一《Biometrika》 接收。  

论文摘要：This paper is concerned with empirical likelihood inference on the population mean when the dimension p and sample size n satisfy p/n-->c in [1,   ）. As shown in Tsao (2004), the empirical likelihood method fails with high probability when p/n > 1/2 because the convex hull of the n observations in Rp becomes too small to cover the true mean value. Moreover, when p > n, the sample covariance matrix becomes singular, and this results in the breakdown of the first sandwich approximation for the log empirical likelihood ratio. To deal with these two challenges, we propose a new strategy of adding two pseudo data points to the observed data. We further establish the asymptotic normality of the proposed empirical likelihood ratio test. The proposed test statistic does not involve the inverse of the sample covariance matrix. Furthermore, its form is explicit, thus the proposed test can easily be carried out with low computational cost.  Our numerical comparison implies that the proposed test outperforms some existing tests for high dimensional mean vectors in terms of power. We also illustrate the proposed procedure by an empirical analysis of stock data.  

崔霞，理学博士，现为广州大学经济与统计学院副教授、副院长。广东省高等学校优秀青年教师培养计划2014年度培养对象，广东省高等学校“千百十人才培养工程”第八批校级培养对象，广州大学第一批学校青年拔尖人才培养对象。中国现场统计学会广东省分会理事；中国现场统计学会资源与环境分会理事。长期致力于半参数模型、高维数据建模、缺失数据分析等方面的研究，在国内外学术刊物上《Annals of Statistics》、《Scandinavian Journal of Statistics》、《Computational Statistics and Data Analysis》、《Science in China Mathematics》发表SCI检索论文10余篇，其中JCR统计学科类期刊一区的有2篇，二区的有6篇，1篇是WOS上的高被引论文。主持完成多项国家自然科学基金、省部级科研项目。