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Submitted by pscully on Mon, 10/13/2008 - 08:28.
10/16/2008 - 16:10
10/16/2008 - 17:30
STA/BST 290: Fang Yao
Functional Mixture Regression
THURSDAY, October 16th, 2008 at 4.10pm, MSB 1147 (Colloquium Room)
Refreshments: 3.30pm, MSB 4110 (Statistics Lounge)
Title: Functional Mixture Regression
Abstract: In classical functional linear models the relationship between the scalar response and the functional predictor process is often assumed to be identical for all subjects. Motivated by both practical and methodological considerations, we relax this assumption and propose a new class of functional regression models that allow the regression structure to vary for different groups of subjects. By applying functional principal component analysis to the predictor process, these new functional regression models are simplified to a framework that is similar to classical mixture regression models. This leads to the proposed approach named as Functional Mixture Regression (FMR).