kader: Kernel Adjusted Density Estimation and Regression

In GerritEichner/kader: Kernel Adaptive Density Estimation and Regression

Description

Package of functions to compute kernel estimators for

• nonparametric density estimation using a data-adjusted kernel or an appropriate rank-transformation, and for

• nonparametric regression using a data-adjusted kernel.

Details

The functions are based on the theory laid out in the following papers:

• Srihera, R., Stute, W. (2011): Kernel adjusted density estimation. Statistics and Probability Letters 81, 571 - 579, URL http://dx.doi.org/10.1016/j.spl.2011.01.013.

• Eichner, G., Stute, W. (2012): Kernel adjusted nonparametric regression. Journal of Statistical Planning and Inference 142, 2537 - 2544, URL http://dx.doi.org/10.1016/j.jspi.2012.03.011.

• Eichner, G., Stute, W. (2013): Rank Transformations in Kernel Density Estimation. Journal of Nonparametric Statistics 25(2), 427 - 445, URL http://dx.doi.org/10.1080/10485252.2012.760737.

A very brief summary of the three papers above and sort of a vignette is presented in Eichner, G. (2017): Kader - An R package for nonparametric kernel adjusted density estimation and regression. In: Ferger, D., et al. (eds.): From Statistics to Mathematical Finance, Festschrift in Honour of Winfried Stute. Springer International Publishing. To appear in Jan. 2018. DOI then(!) presumably: 10.1007/978-3-319-50986-0.

GerritEichner/kader documentation built on May 10, 2019, 1:14 p.m.