STOR Colloquium: Jin-Ting Zhang (Princeton University)

Statistical Inference for Linear Models with Functional Responses

With modern science and technology development, functional responses are observed frequently in many scientific fields such as biology, meteorology, ergonomics among others. Consider statistical inferences for functional linear models in which the response functions depend on a few time-independent covariates, but the covariate effects are functions of time. Of interest is to test a general linear hypothesistesting (GLHT) problem about the covariate effects. In this talk, an F-type test for this GLHT problem is introduced and its asymptotic power is derived. It is shown that the F-type test is root-n consistent. Applications of the F-type test in one-sample, two-sample and k-sample problems, and in variable selections and outlier detections in functional linear models are discussed. The F-type test is illustrated via applications to a real functional data set collected in ergonomics.

Refreshments will be served at 3:30pm in the 3rd floor lounge of Hanes Hall