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Discrete functional data analysis

In: Compstat 2006 - Proceedings in Computational Statistics

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  • Masahiro Mizuta

    (Hokkaido University)

Abstract

In this paper, we try to extend the framework of Functional Data Analysis (FDA). FDA is an exciting theme that continues development in data analysis. We can sometimes find out valuable information through FDA. Most methods on FDA assume that the functions that represent data are differentiable. But we discuss the use of discrete functions for FDA. Discrete functions are indifferentiable of course, but we can use differences of the functions. At first, we construct a new definition of first order and high order differences for discrete functional data analysis. Then we propose a method to look at the structures that the discrete functional data have by utilizing the proposed high order differences.

Suggested Citation

  • Masahiro Mizuta, 2006. "Discrete functional data analysis," Springer Books, in: Alfredo Rizzi & Maurizio Vichi (ed.), Compstat 2006 - Proceedings in Computational Statistics, pages 361-369, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-1709-6_28
    DOI: 10.1007/978-3-7908-1709-6_28
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