fdacluster

Description

Implementations of the k-means, hierarchical agglomerative and DBSCAN clustering methods for functional data which allows for jointly aligning and clustering curves. It supports functional data defined on one-dimensional domains but possibly evaluating in multivariate codomains. It supports functional data defined in arrays but also via the 'fd' and 'funData' classes for functional data defined in the 'fda' and 'funData' packages respectively. It currently supports shift, dilation and affine warping functions for functional data defined on the real line and uses the SRVF framework to handle boundary-preserving warping for functional data defined on a specific interval. Main reference for the k-means algorithm: Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean alignment for curve clustering" <doi:10.1016/j.csda.2009.12.008>. Main reference for the SRVF framework: Tucker, J. D., Wu, W., & Srivastava, A. (2013) "Generative models for functional data using phase and amplitude separation" <doi:10.1016/j.csda.2012.12.001>.

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  installed size is 14.8Mb
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    help   2.1Mb
    libs   8.8Mb

  installed size is 15.6Mb
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Check History

  installed size is 14.8Mb
  sub-directories of 1Mb or more:
    R      1.9Mb
    doc    1.5Mb
    help   2.1Mb
    libs   8.8Mb

  installed size is 15.6Mb
  sub-directories of 1Mb or more:
    R      2.4Mb
    doc    1.5Mb
    help   2.1Mb
    libs   9.1Mb

  installed size is  7.5Mb
  sub-directories of 1Mb or more:
    R      1.8Mb
    doc    1.5Mb
    help   2.1Mb
    libs   1.6Mb

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