Events

Prof. Zhenhua Lin
Presidential Young Professor
Department of Statistics and Data Science
National University of Singapore

Statistical inference is of fundamental importance and yet challenging in high-dimensional and functional data analysis. In response to the challenge, a set of powerful bootstrap-based procedures are developed for high-dimensional ANOVA and two-sample problems. These methodologies are also adapted to test hypotheses and construct simultaneous confidence bands for mean functions, coefficient functions in the varying coefficient model, and slope functions in functional linear regression. The validity and consistency of the proposed procedures are established, and convergence rates are derived. The proposed procedures are shown to enjoy excellent numeric performance, especially when the sample size is limited while the signal is relatively weak.