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Kader—An R Package for Nonparametric Kernel Adjusted Density Estimation and Regression

In: From Statistics to Mathematical Finance

Author

Listed:
  • Gerrit Eichner

    (Justus-Liebig-University Giessen, Mathematical Institute)

Abstract

In a series of three papers published from 2011 through 2013, Stute and coauthors introduced a fully data-adaptive nonparametric kernel method for pointwise univariate density estimation and likewise for regression estimation. For density estimation a robustified version of this adaptive method was also provided and the pointwise method was extended to an $$L_2$$ -approach. Here, an R package is presented that implements (so far) parts of those methods. This package is a first attempt to narrow the gap between the theoretical derivation of the methods and their availability for practical applications.

Suggested Citation

  • Gerrit Eichner, 2017. "Kader—An R Package for Nonparametric Kernel Adjusted Density Estimation and Regression," Springer Books, in: Dietmar Ferger & Wenceslao González Manteiga & Thorsten Schmidt & Jane-Ling Wang (ed.), From Statistics to Mathematical Finance, chapter 0, pages 291-315, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-50986-0_15
    DOI: 10.1007/978-3-319-50986-0_15
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