Discussion of paper "Functional Data Analysis for Sparse Longitudinal Data."


Yan-Wen Shiu
2010-05-21  12:30 - 14:30
Room 405, Mathematics Research Center Building (ori. New Math. Bldg.)

"In this talk, we consider PACE (principal components analysis through conditional expectation) which is a nonparametric method for sparse longitudinal data. The method aims at irregularly spaced longitudinal data, where the number of repeated measurements available per subject is small. First I will make a comparision between MDA and FDA, and then introduce PACE method, illustrated with a simulation study, longitudinal CD4 data for a sample of AIDS patients, e-Bay auction data and time-course gene expression data for the yeast cell cycle. Finally under some mild regularity assumption, we present asympototic properties of this proposed estimation method."

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