Abstract #300749

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JSM 2002 Abstract #300749
Activity Number: 362
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing*
Abstract - #300749
Title: Functional Principal Components Analysis: Rotation and Regression
Author(s): Victor Solo*+ and Sarah Ratcliffe
Affiliation(s): University of New South Wales and University of Pennsylvania
Address: Kensington 2052, Sydney, , 2073, Australia
Keywords: functional data analysis ; nonparametric ; longitudinal data analysis
Abstract:

We give a new "small noise" maximum likelihood motivation for basis expansions based functional principal components analysis (fPCA). This delivers a new exact approach for fPCA when sampling times differ across subjects, involving a rotated PCA. Both mean and random effects are modelled nonparametrically and the fitting algorithm is a simple cyclic descent procedure. A convergence result is developed and some illustrations on data are given.

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Revised March 2002