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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/21199

    Title: Functional Clustering of Longitudinal Data
    Authors: Chiou, Jeng-min;Li, Pai-ling
    Contributors: 淡江大學統計學系
    Date: 2008
    Issue Date: 2009-11-30 13:17:37 (UTC+8)
    Publisher: Heidelberg: Physica-Verlag
    Abstract: This study considers two clustering criteria to achieve difierent goals of grouping similar curves. These criteria are based on the minimal L2 distance and the maximal functional correlation defined in this study, respectively. Each cluster centers on a subspace spanned by the cluster mean and covariance eigenfunctions of the underlying random functions. Clusters can thus be identified by the subspace projection of curves.
    Relation: Functional and Operatorial Statistics, pp.103-107
    DOI: 10.1007/978-3-7908-2062-1_17
    Appears in Collections:[Graduate Institute & Department of Statistics] Chapter

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