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

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From Statistics to Mathematical Finance
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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.

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Thanks to the two referees whose constructive criticism and suggestions helped to improve the paper considerably.

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Correspondence to Gerrit Eichner .

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Eichner, G. (2017). Kader—An R Package for Nonparametric Kernel Adjusted Density Estimation and Regression. In: Ferger, D., González Manteiga, W., Schmidt, T., Wang, JL. (eds) From Statistics to Mathematical Finance. Springer, Cham.

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