TY - JOUR AU - Hofmeyr, David P. PY - 2022/01/31 Y2 - 2024/03/29 TI - Fast Kernel Smoothing in R with Applications to Projection Pursuit JF - Journal of Statistical Software JA - J. Stat. Soft. VL - 101 IS - 3 SE - Articles DO - 10.18637/jss.v101.i03 UR - https://www.jstatsoft.org/index.php/jss/article/view/v101i03 SP - 1 - 33 AB - <p>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 readyto-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.</p> ER -