Functional Response Models

Abstract

We review functional regression models and discuss the situation where the predictor is a vector or scalar such as a dose and the response is a random trajectory. These models incorporate the influence of the predictor either through the mean response function, through the random components of a Karhunen-Loeve or functional principal components expansion, or by means of a combination of both. In a case study, we analyze dose-response data with functional responses from an experiment on the age-specific reproduction of medflies. We compare several functional response models for these data. Some other proposed methods related to functional/longitudinal data analysis will also be discussed in this talk.