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Kader – an R package for nonparametric kernel adjusted density estimation and regression. (English) Zbl 1383.62009
Ferger, Dietmar (ed.) et al., From statistics to mathematical finance. Festschrift in honour of Winfried Stute. Cham: Springer (ISBN 978-3-319-50985-3/hbk; 978-3-319-50986-0/ebook). 291-315 (2017).
Summary: 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.
For the entire collection see [Zbl 1383.62010].
##### MSC:
 62-04 Software, source code, etc. for problems pertaining to statistics 62G07 Density estimation 62G08 Nonparametric regression and quantile regression
##### Software:
feature; Kader; kedd; KernSmooth; ks; lokern; MASS (R); np; R; sm
Full Text:
##### References:
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