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  • ParkAhnBiometrics2016-earlyview

    Rights statement: This is the peer reviewed version of the following article: Park, J. and Ahn, J. (2016), Clustering multivariate functional data with phase variation. Biometrics. doi: 10.1111/biom.12546 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/biom.12546/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Clustering multivariate functional data with phase variation

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>03/2017
<mark>Journal</mark>Biometrics
Issue number1
Volume73
Number of pages10
Pages (from-to)324-333
Publication StatusPublished
Early online date24/05/16
<mark>Original language</mark>English

Abstract

When functional data come as multiple curves per subject, characterizing the source of variations is not a trivial problem. The complexity of the problem goes deeper when there is phase variation in addition to amplitude variation. We consider clustering problem with multivariate functional data that have phase variations among the functional variables. We propose a conditional subject-specific warping framework in order to extract relevant features for clustering. Using multivariate growth curves of various parts of the body as a motivating example, we demonstrate the effectiveness of the proposed approach. The found clusters have individuals who show different relative growth patterns among different parts of the body.

Bibliographic note

This is the peer reviewed version of the following article: Park, J. and Ahn, J. (2017), Clustering multivariate functional data with phase variation. Biom, 73: 324–333. doi:10.1111/biom.12546 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/biom.12546/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.