Functional Data Analysis of Tree Data Objects.

@article{Shen2014FunctionalDA,
  title={Functional Data Analysis of Tree Data Objects.},
  author={Dan Shen and Haipeng Shen and Shankar Bhamidi and Yolanda Mu{\~n}oz Maldonado and Yongdai Kim and J. s. Marron},
  journal={Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America},
  year={2014},
  volume={23 2},
  pages={418-438}
}
Data analysis on non-Euclidean spaces, such as tree spaces, can be challenging. The main contribution of this paper is establishment of a connection between tree data spaces and the well developed area of Functional Data Analysis (FDA), where the data objects are curves. This connection comes through two tree representation approaches, the Dyck path representation and the branch length representation. These representations of trees in Euclidean spaces enable us to exploit the power of FDA to… CONTINUE READING
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