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arXiv · 2001.02225

Fast Kernel Smoothing in R with Applications to Projection Pursuit

David P. Hofmeyr
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Abstract

This paper introduces the R package FKSUM, which offers fast and exact evaluation of univariate kernel smoothers. The main kernel computations are implemented in C++, and are wrapped in simple, intuitive and versatile R functions. The fast kernel computations are based on recursive expressions involving the order statistics, which allows for exact evaluation of kernel smoothers at all sample points in log-linear time. In addition to general purpose kernel smoothing functions, the package offers purpose built and ready-to-use implementations of popular kernel-type estimators. On top of these basic smoothing problems, this paper focuses on projection pursuit problems in which the projection index is based on kernel-type estimators of functionals of the projected density.

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BibTeXRIS

David P. Hofmeyr. 2020-01-07. Fast Kernel Smoothing in R with Applications to Projection Pursuit. https://arxiv.org/abs/2001.02225

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