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Statistics Seminar
Department of Mathematical Sciences

DATE:Thursday, March 10, 2016
TIME:1:15pm to 2:15pm
SPEAKER:Zuofeng Shang, Binghamton University
TITLE:Nonparametric Inference In Functional Data


We propose a roughness regularization approach in making nonparametric inference for generalized functional linear models. In a reproducing kernel Hilbert space framework, we construct asymptotically valid confidence intervals for regression mean, prediction intervals for future response and various statistical procedures for hypothesis testing. In particular, one procedure for testing global behaviors of the slope function is adaptive to the smoothness of the slope function and to the structure of the predictors.

seminars/stat/160310.txt · Last modified: 2016/05/01 21:47 by aleksey