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Properties of principal component methods for functional and longitudinal data analysis

Hall, Peter; Müller, Hans-Georg; Wang, Jane-Ling


The use of principal component methods to analyze functional data is appropriate in a wide range of different settings. In studies of ``functional data analysis,'' it has often been assumed that a sample of random functions is observed precisely, in the continuum and without noise. While this has been the traditional setting for functional data analysis, in the context of longitudinal data analysis a random function typically represents a patient, or subject, who is observed at only a...[Show more]

CollectionsANU Research Publications
Date published: 2006-08-01
Type: Journal article
Source: Annals of Statistics 2006, Vol. 34, No. 3, 1493-1517
DOI: 10.1214/009053606000000272


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