Title: Quadratic regression for functional response models
Authors: Hidetoshi Matsui - Shiga University (Japan) [presenting]
Abstract: The problem of constructing a regression model with a functional predictor and a functional response is considered. We extend the functional linear model to the quadratic model, where the quadratic term also takes the interaction between the argument of the functional data into consideration. We assume that the predictor and the coefficient functions are expressed by basis expansions, and then parameters included in the model are estimated by the maximum likelihood method by assuming that the error function follows a Gaussian process. We apply the proposed method to the analysis of weather data, and then investigate what the results provides.