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This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

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Activity Number: 57
Type: Topic Contributed
Date/Time: Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
Sponsor: IMS
Abstract - #308548
Title: Functional Data Analysis in Lipoprotein Profile Data
Author(s): Yehua Li*+ and Tailen Hsing
Companies: University of Georgia and The Ohio State University
Address: 204 Statistics Building, Athens, GA, 30602,
Keywords: Functional Data Analysis ; linear model ; Kalman filter ; principal component ; projection pursuit ; penalized spline
Abstract:

Lipoprotein concentration in human serum is an important risk factor for cardiovascular heart disease. Different species of lipoprotein in a serum sample can be separated by a centrifugation treatment, according to their density differences. A lipoprotein profile for a patient is obtained by taking the image of his centrifuged serum sample, after an application of a lipophilic stain. In this paper, we use functional data analysis techniques to study the lipoprotein profile curves. The goal is to predict the quantity of total cholesterol and each species of lipoprotein from the profile curves. We discuss implementation issues including smoothing the profile curves with P-spline using the Kalman filter technique, functional PCA and functional linear model. We also study a functional projection pursuit model, as a device to check the adequacy of the functional linear model.

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Revised September, 2007