title: Clustering multivariate functional data with phase variation.
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.
authors.affiliation: Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, UK.
authors.forename: Juhyun
authors.initials: J
authors.lastname: Park
authors.affiliation: Department of Statistics, University of Georgia, Athens, Georgia 30602-1952, U.S.A.
authors.forename: Jeongyoun
authors.initials: J
authors.lastname: Ahn
mesh_terms: D000886:Anthropometry; D001837:Body Weights and Measures; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D018507:Gene Expression Regulation, Developmental; D048788:Growth and Development / Q000235:genetics; D006801:Humans; D015999:Multivariate Analysis
keywords: Curve alignment; Functional clustering; Growth curves; Multivariate functional data; Phase variation