JSM 2003 Online Program

Abstract #300614

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Activity Number:	174
Type:	Contributed
Date/Time:	Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor:	Section on Statistical Computing
Abstract - #300614
Title:	Functional Data Analysis, High-Dimensional Maximum Likelihood, and an Associated EM Algorithm
Author(s):	Victor Solo*+
Companies:	University of New South Wales
Address:	School of Electrical Engineering & Telecommunications, Sydney NSW 2052, , , Australia
Keywords:	functional data analysis ; high dimensional ; nonparametric
Abstract:	We consider nonparametric fitting of a mixed effects model to high-dimensional repeated measures data. We have previously shown that when the number of observations per subject is much larger than the number of subjects the likelihood simplifies to a form whose optimization involves joint (but not separable) functional PCA and functional regression. Here we show how the EM algorithm reduces in this setting to a new and simpler form. An empirical example will be given.

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