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Abstract Details

Activity Number: 227
Type: Topic Contributed
Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #306496
Title: Principal Component Analysis for Multilevel and Multivarate Functional Data
Author(s): Chongzhi Di*+ and Ciprian Crainiceanu
Companies: Fred Hutchinson Cancer Research Center and The Johns Hopkins University
Address: 1100 Fairview Ave N, Seattle, WA, 98109-4433, United States
Keywords: functional data ; principal component analysis

Functional data is becoming increasingly common in health research. As a key technique for such data, functional principal component analysis (FPCA) was designed for a sample of independent functions. In this talk, we extend the scope of FPCA to multilevel and multivariate functional data. We exploit the hierarchical structure of covariance operators at between and within subject levels, and extract dominating modes of variations at each level. The decomposition also allows us to investigate within subject functional correlations. Our approach is motivated by a few applications including the Sleep Heart Health Study.

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